System and method for virtual character creation and mechanics

Abstract

A method generates a virtual character for use in a game. The method includes identifying a first physical object, acquiring a first product identifier associated with the first physical object, acquiring a first product description based on the first product identifier, and generating a first narrative description of a first creature based on the first product description. The method further includes defining at least one characteristic of the first creature distinct from the first narrative description, generating an image of the first creature based on the first narrative description, and storing, in a data store that stores virtual character data for virtual characters playable in a video game, a first data set defining the first creature. The data set includes the defined characteristic of the first creature and the image of the first creature. Also provided is a system for implementing a video game utilizing the virtual character.

Description

Attorney Docket: WRCD 15356WOSYSTEM AND METHOD FOR VIRTUAL CHARACTER CREATION AND MECHANICSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application takes priority from Provisional Patent Application No.63 / 761,315, filed February 21, 2025, the entire contents of which are incorporated by reference herein.FIELD OF THE INVENTION

[0002] The invention is in the field of virtual characters for use in video game applications, in particular, unique methods and systems for creating virtual characters.BACKGROUND

[0003] Video game applications continue to increase in popularity, but games tend to provide a formulaic experience. Further, different players playing an identical game would thereby access the same experience, and if a game is played multiple times, the game experience tends to be similar, if not identical, because all characters and scenarios are based on the same stored content.

[0004] While existing games sometimes have hidden characters or scenarios that are accessed only randomly and rarely, such characters and scenarios are still programmed into the game software and are therefore limited.

[0005] Further, users increasingly desire games that interact with the real world in unique ways. Accordingly, many games implement augmented reality features.However, such augmented reality features tend to be limited, again, to characters or scenarios already anticipated by software programmers and programmed into the game software. In existing implementations of such features, characters or scenarios may then be triggered by a real-world location detected using GPS or a real-world code, such as a barcode or QR code. However, the link to the real world is limited to a link contemplated by a game programmer or a randomized trigger. Accordingly, the real world tends to have a limited impact on gameplay in existing video game applications.Attorney Docket: WRCD 15356WO

[0006] Various Al technologies exist that could artificially populate a virtual environment or could be used to “imagine” a character having desired aesthetics and other characteristics. However, existing use of existing Al platforms to generate characters to populate a virtual world or a video game are typically used as shortcuts to character design. Such an approach might allow a player to instruct a game engine on how to build their character and may be faster and easier than having the player choose individual player characteristics, but it would not provide a link to real world objects, nor would it provide for balanced gameplay.

[0007] There is a need for a video game application in which objects in the real world can impact gameplay in a meaningful way.SUMMARY

[0008] A method is provided for generating a virtual character for use in a game. The method includes identifying a first physical object, acquiring a first product identifier associated with the first physical object, acquiring a first product description based on the first product identifier, and generating a first narrative description of a first creature based on the first product description. The method further includes defining at least one characteristic of the first creature distinct from the first narrative description, generating an image of the first creature based on the first narrative description, and storing, in a data store that stores virtual character data for virtual characters playable in a video game, a first data set defining the first creature. The data set includes the defined characteristic of the first creature and the image of the first creature.

[0009] In some embodiments, the generation of the first narrative description includes providing the first product description to a first machine learning model configured to create a description of physical characteristics of an interactive creature based on a product description.

[0010] In some such embodiments, the first machine learning model is configured to virtually transform the first physical object described by the first product description into the first creature. The first narrative description is then based on the first creature.Attorney Docket: WRCD 15356WO

[0011] In some such embodiments, the first machine learning model is further configured to generate the at least one characteristic of the first creature. The at least one characteristic is based on the first creature but not based on the first narrative description.

[0012] In some such embodiments, the at least one characteristic is a plurality of individual characteristics, and each of the plurality of individual characteristics is selected by the first machine learning model from a predetermined list of values for the corresponding individual characteristic.

[0013] In some such embodiments, different individual characteristics of the plurality of individual characteristics are selected from different predetermined lists of values, and at least one of the plurality of individual characteristics is selected from a ranked list of values.

[0014] In some such embodiments, the method further includes applying an additional characteristic to the first creature, the additional characteristic being defined to at least partially counteract a ranking of the at least one of the plurality of individual characteristics and thereby normalize a quality metric associated with the first creature.

[0015] In some embodiments in which a plurality of individual characteristics are defined, the method includes defining an ability of the first creature, the defining of the ability of the first creature including providing the first narrative description and at least one of the plurality of individual characteristics to the first machine learning model. The first machine learning model is further configured to generate an ability description and at least one ability characteristic associated with the ability, and the first data set then further comprises the ability.

[0016] In some such embodiments, the ability is an attack ability or a defensive ability, and the at least one ability characteristic is selected from a predetermined list of potential individual characteristics.

[0017] In some embodiments utilizing a machine learning model, the first machine learning model is a large language model.Attorney Docket: WRCD 15356WO

[0018] In some embodiments utilizing a machine learning model, the image of the first creature is generated by providing the first narrative description of the first creature to a second machine learning model, where the second machine learning model is configured to generate images based on narrative descriptions.

[0019] In some such embodiments, the second machine learning model is an Al image model.

[0020] In some embodiments utilizing a second machine learning model, the method further includes providing the image of the first creature to a third machine learning model, where the third machine learning model is configured to generate a three dimensional printable model, and generating a physical object from an output of the third machine learning model.

[0021] In some embodiments utilizing a second machine learning model, the method further includes updating the first creature by identifying an enhancement to be applied to the first creature. The enhancement is typically acquired in the context of the video game, and updating the first creature includes generating an updated narrative description by providing the first machine learning model with the first narrative description and providing the first machine learning model with data associated with the enhancement.

[0022] The first machine learning model is further configured to generate an updated first narrative description by incorporating characteristics defined in the data associated with the enhancement into the first narrative description.

[0023] The method then generates an updated image of the first creature by providing the updated first narrative description to the second machine learning model and replacing the image of the first creature with the updated image of the first creature in the first data set.

[0024] In some such embodiments, the enhancement is defined by an item data set for an in-game item, wherein the item data set defines visual characteristics to be modified by a use of the in-game item.Attorney Docket: WRCD 15356WO

[0025] In some embodiments, the method further includes providing a user interface associated with the video game where the first creature is usable as a playable character, and where the behavior of the first creature in the context of the video game is at least partially defined by the characteristic of the first creature.

[0026] In some embodiments, the method further includes generating a second virtual character for use in the game by identifying a second physical object, acquiring a second product identifier associated with the second physical object, acquiring a second product description based on the second product identifier, generating a second narrative description of a second creature based on the second product description, defining at least one characteristic of the second creature distinct from the second narrative description, generating an image of the second creature based on the second narrative description, and storing, in the data store, a second data set defining the second creature. The second data set then includes the at least one characteristic of the second creature and the image of the second creature.

[0027] In some such embodiments, the method further includes providing a first implementation of a user interface associated with the first creature at a first user interface device and a second implementation of the user interface associated with the second creature at a second user interface device. The method then includes initiating, at one of the first user interface device and the second user interface device, a battle between the first creature defined in the first data set and the second creature defined in the second data set.

[0028] The method then applies an in-game battle engine to define a winner of the battle based at least partially on the at least one characteristic of the first creature and the at least one characteristic of the second creature, and indicates the winner of the battle at each of the first user interface device and the second user interface device.

[0029] In some such embodiments, the method includes providing an in-game reward to the winner of the battle, where the in-game reward modifies the at least oneAttorney Docket: WRCD 15356WOcharacteristic of the corresponding creature or is provided in the form of in-game currency.

[0030] In some embodiments, the method includes providing a user interface associated with the video game at a user interface device where the first creature is usable as a playable character, where the first product identifier is machine readable and where acquiring the first product identifier is by scanning the first product identifier at the user interface device. In some such embodiments, the first product identifier is a code for looking up product information and does not encode product information, and the first product description is retrieved from a database based on the first product identifier.

[0031] In some embodiments, the method includes printing the first data set on a card for use in a card based game.

[0032] In some embodiments, the method includes printing the image of the first creature on a physical object.

[0033] Also provided is a system for implementing a video game. Such a system includes a data store that stores virtual character data for virtual characters playable in a video game, a computer readable memory containing instructions for implementing the video game, a first user interface device, and a computing system in communication with the data store and the computer readable memory configured to execute computer-readable instructions. The computing system is then configured to scan, at the first user interface device, a machine readable first product identifier associated with a first physical object, acquire a first product description based on the scanned first product identifier, generate a first narrative description of a first creature based on the first product description, define at least one characteristic of the first creature distinct from the first narrative description, generate an image of the first creature based on the first narrative description, and store, at the data store, a first data set defining the first creature

[0034] The first data set includes the at least one characteristic of the first creature and the image of the first creature.Attomey Docket: WRCD 15356WO

[0035] In some such systems, the system includes a second user interface device, where the computing system is further configured to execute the computer-readable instructions in order to scan, at the second user interface device, a machine readable second product identifier associated with a second physical object, acquire a second product description based on the scanned second product identifier, generate a second narrative description of a second creature based on the second product description, define at least one characteristic of the second creature distinct from the second narrative description, generate an image of the second creature based on the second narrative description, and store, at the data store, a second data set defining the second creature, the second data set.

[0036] The second data set includes the at least one characteristic of the second creature, and the image of the second creature.

[0037] In some embodiments, the computing system is further configured to execute the computer-readable instructions in order to provide a first implementation of a user interface associated with the first creature at the first user interface device and a second implementation of the user interface associated with the second creature at the second user interface device, and to provide a battle system by which a battle between the first creature and the second creature is initiated from one of the first and second user interface devices.BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is an embodiment of a system for creating and using virtual characters in accordance with this disclosure.

[0039] Figure 2 is a method for creating a virtual character.

[0040] Figure 3 is a schematic example of the use of the method of FIG. 2.

[0041] Figure 4 is a series of wireframes showing the creation of a virtual character using the method of FIG. 2.

[0042] Figure 5 A shows a product for use in the method of FIG. 2.Attorney Docket: WRCD 15356WO

[0043] Figure 5B shows an example of a character created using the method of FIG. 2.

[0044] Figure 6 is a method for evolving a character created using the method of FIG. 2.

[0045] Figure 7 is a series of wireframes showing the evolution of a virtual character using the method of FIG. 5.

[0046] Figure 8 shows the character of FIG. 5 following an evolution in accordance with FIG. 6.

[0047] Figure 9 shows various characters created using the method of FIG. 2.

[0048] Figures 10 and 11 show the evolution of a character from FIG. 9 using the method of FIG. 5.

[0049] Figure 12 is a method for implementing a virtual battle using characters created using the method of FIG. 2.

[0050] Figure 13 shows an initiation of a battle in accordance with the method of FIG. 12.

[0051] Figure 14 shows the result of the battle of FIG. 13.

[0052] Figure 15 shows the implementation of a battle engine in the battle of FIG.13.DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0053] The description of illustrative embodiments according to principles of the present invention is intended to be read in connection with the accompanying drawings, which are to be considered part of the entire written description. In the description of embodiments of the invention disclosed herein, any reference to direction or orientation is merely intended for convenience of description and is not intended in any way to limit the scope of the present invention. Relative terms such as “lower,” “upper,” “horizontal,” “vertical,” “above,” “below,” “up,” “down,” “top” and “bottom” as well as derivative thereof (e.g., “horizontally,” “downwardly,” “upwardly,” etc.) should be construed to refer to the orientation as then described or as shown in the drawing under discussion.Attorney Docket: WRCD 15356WOThese relative terms are for convenience of description only and do not require that the apparatus be constructed or operated in a particular orientation unless explicitly indicated as such. Terms such as “attached,” “affixed,” “connected,” “coupled,” “interconnected,” and similar refer to a relationship wherein structures are secured or attached to one another either directly or indirectly through intervening structures, as well as both movable or rigid attachments or relationships, unless expressly described otherwise. Moreover, the features and benefits of the invention are illustrated by reference to the exemplified embodiments. Accordingly, the invention expressly should not be limited to such exemplary embodiments illustrating some possible non-limiting combination of features that may exist alone or in other combinations of features; the scope of the invention being defined by the claims appended hereto.

[0054] This disclosure describes the best mode or modes of practicing the invention as presently contemplated. This description is not intended to be understood in a limiting sense, but provides an example of the invention presented solely for illustrative purposes by reference to the accompanying drawings to advise one of ordinary skill in the art of the advantages and construction of the invention. In the various views of the drawings, like reference characters designate like or similar parts.

[0055] Many video games enable a player to select from predefined playable characters with defined characteristics. Such players may be directly accessible to a player, or they may be randomly assigned to a player. Similarly, such defined characteristics may be programmed along with a character design, or they may be randomly or pseudo-randomly generated. Further, a player may be able to customize a character by modifying aesthetic aspects of the character and / or defining characteristics for the character. Player modifications of characteristics for playable characters is typically limited in order to ensure game balance. As such, a player may choose to make their character stronger at the expense of agility or defensive characteristics.

[0056] Existing Al platforms could be used to generate customized characters based on characteristics or descriptions provided by either a player or a programmer.Attorney Docket: WRCD 15356WOHowever, users may want a unique video game character and experience tied to the real world in some way.

[0057] The methods provided herein allow users to link their instance of a video game to the real world by scanning product identifiers from real world physical objects. For example, a user may scan a barcode from a product, and the methodology may then create a character based on the product from which the product identifier was retrieved. In this way, all aspects of the character, from its aesthetics to its functional characteristics, such as statistics and attributes, may be tied to the product used to seed the character.

[0058] The method further provides an evolution engine for evolving characters while maintaining the fundamental connection to the product used to seed the character.

[0059] Figure 1 is an embodiment of a system 100, or overall computing environment, for creating and using virtual characters in accordance with this disclosure. As shown, the system 100 typically includes one or more data store 110 that stores virtual character data in the form of data sets for virtual characters playable in a video game, and a computer readable memory 120 containing instructions for implementing the corresponding video game. The data store 110 may be included within the readable memory 120, such that the game data is largely self-contained, or the data store 110 may be an independent database.

[0060] The system 100 then further includes a first user interface device 130a and a second user interface device 130b and a computing system 140 in communication with the data store 110 and the computer readable memory 120. For example, the computing system 140 may be a server on which a game leveraging the characters from the data store 110 is implemented.

[0061] Where the computing system 140 is a server hosting a game, the computer readable memory 120 may be memory associated with or integrated into the server, and the data store 110 may similarly be memory associated with the server. Alternatively, all components of the game may be distributed such that the computing system 140 is aAttorney Docket: WRCD 15356WOvirtual server providing access to users. The computing system 140 typically has processing circuitry 150, such as a processor, which may be configured and utilized to execute computer-readable instructions stored in the computer-readable memory to implement the methods described herein.

[0062] The first user interface device 130a and the second user interface device 130b may communicate with the computing system 140 and with each other by way of a network 160, such as the internet. Accordingly, the computing system 140 typically has a communication interface 155, such as an internet connection interface. While only one network 160 is shown, it is understood that multiple distinct and / or distributed networks may be utilized in order to facilitate the methods described herein. Similarly, while the computing system 140 is shown as a single entity, such as a server, it could be a virtual server in which different computing assets associated with the computing system are themselves in contact with each other by way of the network 160.

[0063] The user interface devices 130a, b are each devices on which individual users, or players, can access the game. Such devices 130a, b may be smartphones or other devices providing network access, such as personal computers, laptops, or other personal devices. Accordingly, each such device typically includes its own memory 170 for storing application data associated with the game, processing circuitry 180 for executing instructions stored in the memory 170, and a user interface 190 by which a user can interact with the software application. Each device 130a, b further includes a communication module 200 by which it may access the network 160 and may thereby communicate with the computing system 140.

[0064] Each device 130a, b typically further includes a display 205 as part of its user interface along with a means for interacting with the application, such as a touch screen 210. Each device 130a, b further includes scanning hardware 220 for retrieving the product identifiers associated with products 230 as described herein. Such scanning hardware 220 may be a camera, or it may be, e.g., a dedicated barcode scanner or other imaging hardware. Similarly, the scanning hardware 220 may be other data acquisitionAttorney Docket: WRCD 15356WOhardware and may thereby acquire data by way of, e.g., near-field communication (NFC), Bluetooth, including low energy variants, and other technologies.

[0065] Additional software modules may be utilized, either as part of the instructions associated with the video game or as external modules. Accordingly, while the software modules are shown as external modules accessed by way of the network 160, the external modules could either be combined or could be incorporated into the computing system 140 itself.

[0066] Accordingly, where the product identifier utilized in the context of the method is provided in the form of a barcode, a universal product code (UPC) service or database 240 may be utilized. Such a service or database 240 may be a simple lookup table or it may be a more active service maintained by a third party.

[0067] Similarly, various Al models implemented by and operated by third parties may be utilized in the course of the method described herein. As such, a large language model (LLM) service 250, such as OpenAI, may be utilized for processing some data, and an independent Al image model service 260, such as Flux, may be utilized for processing some data. In some embodiments, the same service may operate both the LLM 250 and the Al image model 260, and because the Al field is rapidly evolving, such services may be provided in various combinations and may take a variety of forms in the future.

[0068] Figure 2 is a method for creating a virtual character. Figure 3 is a schematic example of the use of the method of FIG. 2. Figure 4 is a series of wireframes 400, 410, 420 showing the creation of a virtual character using the method of FIG. 2. Figure 5A shows a product 230 for use in the method and Figure 5B shows an example of a character 500 created using the method of FIG. 2 based on the product 230.

[0069] As shown, a method is provided for generating a virtual character 500 for use in a game. The method includes first identifying (300) a first physical object. The physical object may be, e.g., a commercial product 230 and it may be provided with a barcode 510. In an example described herein, the physical object 230 may be a bag ofAttorney Docket: WRCD 15356WOnacho cheese tortilla chips 230, for example, and the bag may be provided with a barcode 510 representing a UPC.

[0070] Accordingly, once the first physical object 230 is identified (at 300), the method proceeds with acquiring a first product identifier (310) by identifying and acquiring the barcode 510 on the bag of nacho cheese tortilla chips 230 and scanning it using the scanning hardware 220 on a user’s interface device 130a. This is shown in FIG.4 at screen 400. Once identified and acquired, the method proceeds to acquire a first product description (320) based on the first product identifier 510. An image of the product 430 may then be presented to a user along with a product name 440 and product description 450 at screen 410.

[0071] Accordingly, the first product identifier (310) may be a barcode 510 scanned by a user. The first product identifier (310) may therefore be a code for looking up product information, such as a UPC code, but may not encode product information itself. Accordingly, once scanned, the first product description may be acquired (320) by submitting a query to a UPC lookup service 240. Alternatively, a computing environment 100 in which the method is implemented may maintain a standalone lookup table for associating UPC codes with product descriptions. In any event, retrieving product descriptions 440 may result in a product name, in this case, “Doritos Nacho Cheese Tortilla Chips, 1.75 Oz Bag,” along with a narrative description of the product. In this case, the description would be “The chip that packs a flavorful punch with the classic crunch. Boldly seasoned with three cheeses, tomatoes, onions and a savory blend of spices. Indulge yourself or share with large gatherings.”

[0072] Accordingly, the description may be provided by a manufacturer of the product, and as a result, may include some subjective language describing the product. However, the description would typically be of an object, such as a food item, and not of a creature or monster with corresponding physical characteristics.

[0073] Following the acquisition of the first product description 440 (at 320), a user may choose to spawn a character based on the product described. In the context of aAttorney Docket: WRCD 15356WOuser interface 190, the user may then select a button 460 in screen 410 that initiates the spawning of the creature. The method proceeds with generating a virtual character, referred to herein as a creature (330) and a first narrative description of a first creature (340) based on the first product description. In doing so, a query may be submitted to a first machine learning model or Al model, such as a large language model (LLM) 250. One example of such a model is that provided by OpenAI, but other LLMs providing interfaces that output structured data may be utilized as well.

[0074] For example, the first machine learning model may be configured to create a description of physical characteristics of an interactive creature based on a provided product description, and the query submitted to the LLM 250 may include the first product description. In some embodiments, the first machine learning model may be configured to virtually transform the first physical object described by the first product description into a creature virtually (at 330). The first machine learning model may then proceed to generate the first narrative description based on the first creature (at 340).

[0075] Accordingly, the first machine learning model 250 may be instructed to proceed in two stages, first creating the creature (at 330) and only then proceeding to generate and provide the narrative description (at 340). The narrative description would then be a physical description of aesthetic properties of the generated, or “imagined” virtual creature. Such a machine learning model 250 may be designed to generate an internal structure or image of the creature without presenting the same to a user, or without being able to present the same to a user, as no image driver may be available to it. Such a machine learning model may then only be able to create a narrative description of the underlying structure or image.

[0076] A prompt or query utilized to generate the narrative description (at 340) by way of the first machine learning model 250 may include substantial limitations, thereby instructing the first machine learning model to create a creature for a game by “transforming” the product into the creature, where such a creature is to be used for head to head battles with other similarly created creatures. The machine learning model 250Attorney Docket: WRCD 15356WOmay be instructed to create content appropriate for all ages and to avoid “not safe for work” elements, and to generate only original content.

[0077] Accordingly, when provided with the product description indicated above corresponding to the nacho cheese tortilla chips, the first machine learning model 250 may output, as a first narrative description (at 340) “A vibrant creature resembling an oversized, angular tortilla chip with a golden-yellow, speckled exterior. Its body is flat and slightly curled, giving it a dynamic pose. The creature's surface is dotted with deep orange and red textures representing spices and cheese. Large, luminescent eyes shimmer with a savory glint, and its limbs end in jagged, shard-like protrusions, resembling broken chip edges. It stands amidst a backdrop of crumbled chip debris, exuding an aura of cheesy energy.”

[0078] In addition to the first narrative description (generated at 340), the first machine learning model may further be used to define at least one characteristic of the virtual creature (350) distinct from the first narrative description. Accordingly, the characteristic may be based on the same “imagined” virtual creature as the narrative description, but does not take the narrative description as input.

[0079] Such a characteristic of the first creature may correspond to a category describing the creatures behavior in the context of an interaction with a second creature. For example, the characteristic may be, e.g., agility in battle or resistance to a category of attack.

[0080] For example, in some embodiments, the creature generated (at 330) is for use in a role playing game or other game category. Accordingly, the at least one characteristic may be a set of characteristics defining the creature so that it can compete in the context of such a role playing game. As such, the at least one characteristic may include, e.g., skills, attributes, and abilities of the creature. In some embodiments, the first machine learning model 250 may also be used to generate a name for the creature.

[0081] In the example described here, the first large language model 250 may then provide the following as output:Attorney Docket: WRCD 15356WO

[0082] name: “Nachoraptor”

[0083] physicalDescription: A vibrant creature resembling an oversized, angular tortilla chip with a golden-yellow, speckled exterior. Its body is flat and slightly curled, giving it a dynamic pose. The creature's surface is dotted with deep orange and red textures representing spices and cheese. Large, luminescent eyes shimmer with a savory glint, and its limbs end in jagged, shard-like protrusions, resembling broken chip edges. It stands amidst a backdrop of crumbled chip debris, exuding an aura of cheesy energy.

[0084] agility: High

[0085] damageType: Magic

[0086] weakness: Water

[0087] resistance: Fire

[0088] powerRank: Veteran

[0089] armor: None

[0090] Each characteristic generated by the first machine learning model 250 is in response to a particular query or prompt, or a particular portion of a query or prompt, submitted to the model and requesting a structured response. Accordingly, the query may narrowly limit the parameters of each individual characteristic once the underlying creature is “imagined” (at 330). It is understood that various machine learning and Al models function in different ways, and the creation, generation, or “imagining” of the creature (at 330) may mean different things in different models. For the purpose of this discussion, the creation of the creature is intended to correspond to the creation of a data structure representing the creature from which other data can be developed or extracted.

[0091] Accordingly, the machine learning model may be configured, either inherently or by the query, to limit an output for an “agility” characteristic to “Low,” “Moderate,” or “High.” Similarly, the damageType may be limited to a set of categories, such as "Fire", "Water", "Earth", "Wind", "Electric", "Ice", “Magic,” etc. In some embodiments, certain characteristics may be linked to each other. For example, damageType, weakness, and resistance may be selected from the same set of categories,Attorney Docket: WRCD 15356WOwhich in turn allows creatures to interact with each other (i.e., by matching one creature’s strengths against another creature’s weaknesses). Accordingly, a creatures “resistance” may be a damage type that the creature is resistant to, and it may therefore be more effective when competing with a character that generates that same damageType.

[0092] Accordingly, the at least one characteristic may be a plurality of individual characteristics, and each of the individual characteristics is then selected by the first machine learning model (at 350) from a predetermined list of values for the corresponding individual characteristics.

[0093] In some cases, different individual characteristics of the plurality of individual characteristics may be selected from different predetermined lists of values, and at least one such characteristic is selected from a ranked list of values. For example, the “powerRank” may be selected from a ranked list including "Novice", "Veteran", "Elite", and the “armor” characteristic may be selected from a ranked list including "None", "Light", "Medium", "Heavy."

[0094] Accordingly, some characteristics are neutral but define likely results in the context of specific interactions, such as a category of attack and a category of weakness. Other characteristics are inherently positive or negative in the context of a game in which the creature will be used.

[0095] In some embodiments, after the initial set of characteristics have been defined, the first machine learning model 250 may be used to define a specific ability of the first creature (360). The specific ability of the creature (defined at 360) may be defined based on both the first narrative description (defined at 340) and at least one of the plurality of individual characteristics (defined at 350). Accordingly, both of those elements may be provided to the first machine learning model 250 as input.Alternatively, a different machine learning model or a differently configured machine learning model may be used as well.Attorney Docket: WRCD 15356WO

[0096] If used to define the specific ability (at 360), the first machine learning model may then be further configured to generate an ability description (at 363) and at least one ability characteristic (at 366) associated with the ability.

[0097] The ability (defined at 360) may be an attack ability or a defensive ability, such that the creature may have a creature specific attack ability. Such a special attack or defensive ability may have an ability characteristic that maps to a creatures standard attack categories, and may therefore be generated from similar predetermined lists to those discussed above. For example, a type of damage may be selected from the same set of categories discussed above. Other ability characteristics may be generated from ranked lists in the same manner discussed above. Accordingly, damage of a specific category may be assigned an amount of damage and / or an accuracy level from a ranked list.

[0098] In some embodiments, special abilities may be tuned based on one or more of the individual characteristics (defined at 350), which may allow the creature to be tuned or moderated in order to balance their performance in a game. Accordingly, for example, if the characteristics (defined at 350) define a particularly powerful creature, such as a creature with a high level of armor, the machine learning model 250 may be more likely to generate a less powerful specific ability (at 360), while a weaker creature may be provided with a more powerful specific ability.

[0099] In some embodiments, the first machine learning model 250 may be asked to base the description of the specific ability (generated at 363) on the first narrative description (generated at 340) and may similarly use that input to generate a name for the ability, along with various ability characteristics (generated at 363). The secondary input of the at least one characteristic (generated at 350) may be used to fine tune the strength of the specific ability (i.e., one or more of the characteristics generated at 363). In the example described here, the first large language model 250 may then provide the following as output:

[0100] name: Savory SurgeAttorney Docket: WRCD 15356WO

[0101] description: The creature channels its cheesy energy, causing its jagged protrusions to glow brightly as it unleashes a torrent of vibrant, swirling magic in the form of spicy energy waves that crash towards its target, leaving shimmering trails of light in their wake.

[0102] damageType: Magic

[0103] damageAmount: Low

[0104] accuracy: High

[0105] The method then proceeds to generate an image of the first creature (370) based on the first narrative description (generated at 340). This may be by providing the first narrative description of the first creature generated by the first machine learning model 250 (at 340) and submitting it as part of a query to a second machine learning model, which may be an Al image model 260, such as Flux. Other Al image models are contemplated as well, but the second machine learning model 260 is typically configured to generate images based on narrative descriptions.

[0106] The second machine learning model 260 may be configured inherently and / or by way of an input prompt or query. Such configuration may provide for family friendly output, as discussed above, along with other characteristics that may lend the image output of the creature a consistent appearance (i.e., dark background, similar light, similar style, such as photorealism, forward facing, etc.). Accordingly, various parameters may be provided as part of a prompt to normalize the output and create consistent creature images. The first narrative description (generated at 340) is then the input used to generate the image (at 370) in the context of those parameters.

[0107] Accordingly, when provided with the first narrative description indicated above, the second machine learning model 260 may output the image shown in FIG. 5B (at 370).

[0108] Following the generation of the image of the first creature (at 370), the method then proceeds to store data associated with the creature in a data store, such as in the data store 110, that stores virtual character data for virtual characters playable in aAttorney Docket: WRCD 15356WOvideo game. A first data set defining that creature may then be stored (380), with the first data set comprising the at least one characteristic of the first creature (generated at 350) and the image of the first creature (generated at 370). In some embodiments, the name, narrative description, and complete list of characteristics may be stored as part of the first data set as well. Where specific abilities are generated (at 360), details associated with the specific ability may be stored in the data set as well.

[0109] The data set may be presented to a user in a character screen 420, shown in FIG. 4, which may include the image of the character 500 of FIG. 5B.

[0110] In some embodiments, in a final step, an overarching characteristic may be utilized to further balance characters across the game environment. For example, hit points may be excluded from the initial generation of characteristics for the creature (at 350) and may be deferred until after the creation of the specific ability (at 360). Hit points may then be calculated based on the characteristics of the creature (at 350) and the ability characteristics (generated at 366). The method may then proceed to calculate hit points (390) based on, e.g., agility, attack accuracy, and damage, so that all creatures are somewhat balanced. Some randomness may be incorporated to generate different strength monsters, within a reasonable range. This calculation (at 390) may be based on a formula or a lookup table and variance may be incorporated in various ways.

[0111] In some embodiments, other characteristics may be randomly modified as well. For example, in some embodiments, weakness may be randomly removed (i.e., with a .05% chance).

[0112] As discussed above, the data set generated and stored 380 as a result of the method of FIG. 2 defines a creature 500 usable as a playable character in a video game. Accordingly, the method may further comprise providing (at 395) a user interface 190 to a user associated with the video game wherein the first creature 500 is a playable character. The user interface 190 may be accessed by the user at the first interface device 130a. The behavior of the first creature 500 in the context of the video game is then atAttorney Docket: WRCD 15356WOleast partially defined by the at least one characteristic (generated at 350) of the corresponding creature.

[0113] As discussed above, the methods described herein are for use in the context of a video game wherein the creatures generated by the method of FIG. 2 are playable characters in the video game. As such, multiple virtual characters, or creatures, may be created for use in the game.

[0114] The method may then further allow for multiple iterations of the method of FIG. 2 in order to create additional creatures. Accordingly, the method may proceed to identify a second physical object (at 300), identifying or acquiring a second product identifier associated with the second physical object (at 310), and acquiring a second product description (340) of the second creature based on the second product description.

[0115] The method may then similarly define at least one characteristic of the second creature distinct from the second narrative description (at 350).

[0116] The method may then generate an image of the second creature (at 370) based on the second narrative description (generated at 350).

[0117] The method may then proceed to store (at 380), in the data store 110, a second data set defining the second creature, where the second data set includes the at least one characteristic of the second creature and the image of the second creature.

[0118] It is understood that all of the details associated with the creation of the first creature 500 could similarly be applied to the creation of the second creature, thereby resulting in multiple distinct but parallel creatures. As discussed above, various approaches may be taken to normalize and balance the multiple creatures, such that in the context of the game, the creatures can fairly do battle against each other.

[0119] Figure 6 is a method for evolving a character created using the method of FIG. 2. Figure 7 is a series of wireframes 400, 410, 420, 700, 710 showing the evolution of a virtual character using the method of FIG. 5. Figure 8 shows the character 500 of FIG. 5 evolved into an updated character 800 following an evolution in accordance with FIG. 6.Attorney Docket: WRCD 15356WO

[0120] As shown, a character 500 is initially created in the same manner as discussed above in reference to FIGS. 2-5. Accordingly, wireframes 400, 410, and 420 show the creation of the character 500 shown in FIG. 5. Following such creation, the method may proceed to update the first creature 500 by identifying an enhancement (at 600) to be applied to the first creature 500.

[0121] The enhancement typically would have been acquired in the context of the video game. Such an acquisition may be by way of gameplay, or it may be by way of an in game purchase. The enhancement may be provided in the context of an in game item 720 selected from multiple available in game items 720, 730, 740. Such an in game item 720 may then be defined by an item data set 750 used to describe the impact of applying that item to a creature 500 as an enhancement (at 600). The item data 750 may then include defined visual characteristics to be modified by the use of the corresponding in game item 720 with the character 500.

[0122] For example, the item data 750 may define an item as follows:

[0123] name: Inferno Potion

[0124] description: The Inferno Potion will transform your monster into a fiery inferno.

[0125] aiPrompt: “Take the following creature description and subtly enhance its appearance to give it a fiery, molten theme, while preserving its original shape, size, and key attributes. Add elements like glowing cracks resembling molten lava, ember-like textures, flame-like patterns, and ash-covered surfaces. Incorporate a fiery color palette with shades of red, orange, and glowing yellow, ensuring the creature retains its distinct form and identity. Avoid making drastic changes to its anatomy, but emphasize the sense of heat, flame, and smoldering power”

[0126] Accordingly, the method may then proceed by providing (610) the first machine learning model 250 with the first narrative description (generated at 340) and additionally providing (620) the first machine learning model 250 with the item data 750 corresponding to the selected item 720. The first machine learning model 250 is thenAttorney Docket: WRCD 15356WOconfigured to generate an updated first narrative description (630) by incorporating characteristics defined in the item data 750 into the first narrative description.

[0127] In the example shown, the updated narrative description (generated at 630) may be:

[0128] A vibrant creature resembling an oversized, angular tortilla chip, but enhanced with a fiery molten theme. Its golden-yellow, speckled exterior is now interspersed with glowing cracks resembling molten lava, glowing bright red and orange beneath the surface. The body remains flat and slightly curled, giving it a dynamic pose, while ember-like textures and ash-covered surfaces create a sense of heat. Flame-like patterns flicker across its surface, enhancing the fiery color palette with shades of red, orange, and glowing yellow. Large, luminescent eyes shimmer with a savory glint, now surrounded by glowing embers, while its jagged, shard-like limbs exude a smoldering power. It stands amidst a backdrop of crumbled chip debris, enhanced with glowing ash, exuding an aura of cheesy but passionate energy.

[0129] During the updating process, a display or animation may be presented to the user at 710 in order to illustrate the evolution of the creature.

[0130] The updated first narrative description (generated at 630) typically describes the physical appearance of the creature, as discussed above. Accordingly, the updated first narrative description may then be provided to the second machine learning model 260 (640) which generates (650) a corresponding updated image 800 of the first creature 500 based on the updated first narrative description. The image of the first creature 500 is then replaced (660) with the updated image of the first creature 800 in the first data set. In enhancing the creature 500, 800 in this way, characteristics of the creature may be updated as well (at 660) in a manner defined by the item data 750.

[0131] Figure 9 shows various creatures 900, 910, 920, 930, 940 created using the method of FIG. 2. All creatures shown were generated based on grocery store products, while different products may generate radically different creatures. Accordingly, Salsaroth 900 is based on ajar of salsa, Saltium 910 is based on salt, and Oliva VenturaxAttorney Docket: WRCD 15356WO920 is based on a jug of olive oil. However, the method may generate different creatures based on the same source product. As such, Salsalticus 940 is based on the same package of salt as Saltium 910.

[0132] Figures 10 and 11 show the evolution of a character 940, 1100 from FIG.9 using the method of FIG. 5. As shown, the application of a sword 1110 to Salsalticus 950 results in a creature 1100 that is fundamentally the same but has a modified visual appearance and has an attack enhanced in a manner defined by the specific item 1110 applied.

[0133] Figure 12 is a method for implementing a virtual battle using characters created using the method of FIG. 2. As discussed above, multiple virtual characters, or creatures may be created using the method of FIG. 2 and such creatures may be enhanced using the method of FIG. 6. Different users may then create or be provided with their own virtual characters or creatures which they can then choose to place into battle with each other.

[0134] Accordingly a first implementation of a user interface 190 may be provided (1200) to a first user at a first user interface device 130a. The first user interface device 130a may include scanning hardware 220. The first product identifier 510 may then machine readable and could be acquired (at 310) by scanning the first product identifier at the user interface device. For example, the first user may have created the creature 500 by scanning the barcode 510 on a physical object 230 by way of the scanning hardware 220 of the interface device 130a. The first implementation of the user interface 190 may then be associated with the first creature 500. For example, such association may be by way of a user account defining creatures created by or associated with a particular user.

[0135] A second user interface 190 may then be provided (1210) to a second user at a second user interface device 130b. The second implementation may be similar, and may be associated with a second creature in the same way. Accordingly, as noted above, a second creature may be created in the same way as the first creature and mayAttorney Docket: WRCD 15356WOcorrespond with and be defined by a second data set in much the same way as the first creature corresponds with and is defined by the first data set.

[0136] Either user may then utilize their own user interface device 130a, b to initiate a battle (1230). Such a battle would then be between the first creature defined by the first data set and the second creature defined by the second data set.

[0137] The method then proceeds to apply an in-game battle engine (1240) to define a winner of the battle based at least partially on the at least one characteristic of the first creature and the at least one characteristic of the second creature as defined in their corresponding data sets.

[0138] The method then indicates (1250) the winner of the battle defined by the in-game battle engine (at 1240) at each of the first and second user interface devices 130a, b.

[0139] Following a battle (at 1240), the method may provide an in-game reward (1260) to the winner of the battle. The in-game reward may modify the at least one characteristic of the corresponding creature. Alternatively, or in addition, the in-game reward may be provided in the form of in-game currency.

[0140] Figure 13 shows an initiation of a battle (1230) in accordance with the method of FIG. 12. Figure 14 shows the result of the battle of FIG. 13 (generated at 1250). Figure 15 shows the implementation of a battle engine (at 1240) in the battle of FIG. 13.

[0141] In addition to the use of the creatures created using the methods of FIG. 2 and 5 in the context of a video game, the method may further comprise printing the first data set onto a card for use in a card based game or for use as a trading card. The method may then further comprise printing the second data set onto a card, thereby facilitating the use of the cards in a card based battle game.

[0142] Further, the first data set or the second data set may be utilized to create additional creature based products. For example, the data set may be transformed into code usable by a 3D printer, such that 3D models of such a creature may be created.Attorney Docket: WRCD 15356WOSimilarly, the data set may be used to print creature themed products, such as cups or articles of clothing.

[0143] The term “data processing apparatus” and like terms encompass all kinds of apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, a system on a chip, or multiple ones, or combinations, of the foregoing. The apparatus can include special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit). The apparatus can also include, in addition to hardware, code that creates an execution environment for the computer program in question, e g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of them. The apparatus and execution environment can realize various different computing model infrastructures, such as web services, distributed computing and grid computing infrastructures.

[0144] A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and it can be deployed in any form, including as a standalone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

[0145] The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computerAttorney Docket: WRCD 15356WOprograms to perform actions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit).

[0146] Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, e.g., a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device (e.g., a universal serial bus (USB) flash drive), to name just a few. Devices suitable for storing computer program instructions and data include all forms of non volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto optical disks; and CD ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

[0147] To provide for interaction with a user, embodiments of the subject matter described in this specification can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer. Computers may furtherAttorney Docket: WRCD 15356WObe provided in other forms, such as in the form of handheld devices or smartphones, as well as in the form of tablet devices. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to and receiving documents from a device that is used by the user; for example, by sending web pages to a web browser on a user’s client device in response to requests received from the web browser. A device for providing interaction with a user may be referred to as a user interface device.

[0148] Embodiments of the subject matter described in this specification can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e g., an application server, or that includes a front end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification, or any combination of one or more such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), an inter-network (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks).

[0149] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In some embodiments, a server transmits data (e.g., an HTML page) to a client device (e.g., for purposes of displaying data to and receiving user input from a user interactingAttorney Docket: WRCD 15356WOwith the client device). Data generated at the client device (e.g., a result of the user interaction) can be received from the client device at the server.

[0150] While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any inventions or of what may be claimed, but rather as descriptions of features specific to particular embodiments of particular inventions. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

[0151] Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0152] While the present invention has been described at some length and with some particularity with respect to the several described embodiments, it is not intended that it should be limited to any such particulars or embodiments or any particular embodiment, but it is to be construed with references to the appended claims so as to provide the broadest possible interpretation of such claims in view of the prior art and, therefore, to effectively encompass the intended scope of the invention. Furthermore, theAttorney Docket: WRCD 15356WOforegoing describes the invention in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial modifications of the invention, not presently foreseen, may nonetheless represent equivalents thereto.

Claims

Attorney Docket: WRCD 15356WOWhat is claimed is:

1. A method for generating a virtual character for use in a game comprising:identifying a first physical object;acquiring a first product identifier associated with the first physical object; acquiring a first product description based on the first product identifier; generating a first narrative description of a first creature based on the first product description;defining at least one characteristic of the first creature distinct from the first narrative description;generating an image of the first creature based on the first narrative description; andstoring, in a data store that stores virtual character data for virtual characters playable in a video game, a first data set defining the first creature, the data set comprising:the at least one characteristic of the first creature; andthe image of the first creature.

2. The method of claim 1 wherein the generation of the first narrative description comprises providing the first product description to a first machine learning model configured to create a description of physical characteristics of an interactive creature based on a product description.

3. The method of claim 2 wherein the first machine learning model is configured to virtually transform the first physical object described by the first product description into the first creature, and wherein the first narrative description is based on the first creature.

4. The method of claim 3 wherein the first machine learning model is further configured to generate the at least one characteristic of the first creature, and wherein the at least one characteristic is based on the first creature but not based on the first narrative description.Attorney Docket: WRCD 15356WO5. The method of claim 4 wherein the at least one characteristic is a plurality of individual characteristics, and wherein each of the plurality of individual characteristics is selected by the first machine learning model from a predetermined list of values for the corresponding individual characteristic.

6. The method of claim 5 wherein different individual characteristics of the plurality of individual characteristics are selected from different predetermined lists of values, and wherein at least one of the plurality of individual characteristics is selected from a ranked list of values.

7. The method of claim 6 further comprising applying an additional characteristic to the first creature, the additional characteristic being defined to at least partially counteract a ranking of the at least one of the plurality of individual characteristics and thereby normalize a quality metric associated with the first creature.

8. The method of claim 5 further comprising defining an ability of the first creature, the defining of the ability of the first creature comprising providing the first narrative description and at least one of the plurality of individual characteristics to the first machine learning model, and wherein the first machine learning model is further configured to generate an ability description and at least one ability characteristic associated with the ability, and wherein the first data set further comprises the ability.

9. The method of claim 8 wherein the ability is an attack ability or a defensive ability, and wherein the at least one ability characteristic is selected from a predetermined list of potential individual characteristics.

10. The method of claim 2 wherein the first machine learning model is a large language model.

11. The method of claim 2 wherein the image of the first creature is generated by providing the first narrative description of the first creature to a second machine learning model, wherein the second machine learning model is configured to generate images based on narrative descriptions.Attorney Docket: WRCD 15356WO12. The method of claim 11 wherein the second machine learning model is an Al image model.

13. The method of claim 11 further comprising providing the image of the first creature to a third machine learning model, wherein the third machine learning model is configured to generate a three dimensional printable model, and generating a physical object from an output of the third machine learning model.

14. The method of claim 11 further comprising updating the first creature by identifying an enhancement to be applied to the first creature, the enhancement being acquired in the context of the video game, wherein the updating of the first creature comprises:generating an updated narrative description by:providing the first machine learning model with the first narrative description; andproviding the first machine learning model with data associated with the enhancement,wherein the first machine learning model is further configured to generate an updated first narrative description by incorporating characteristics defined in the data associated with the enhancement into the first narrative description; and generating an updated image of the first creature by:providing the updated first narrative description to the second machine learning model, andreplacing the image of the first creature with the updated image of the first creature in the first data set.

15. The method of claim 14 wherein the enhancement is defined by an item data set for an in-game item, wherein the item data set defines visual characteristics to be modified by a use of the in-game item.

16. The method of claim 1 further comprising providing a user interface associated with the video game wherein the first creature is usable as a playable character, andAttorney Docket: WRCD 15356WOwherein the behavior of the first creature in the context of the video game is at least partially defined by the at least one characteristic of the first creature.

17. The method of claim 1 further comprising generating a second virtual character for use in the game by:identifying a second physical object;acquiring a second product identifier associated with the second physical object; acquiring a second product description based on the second product identifier; generating a second narrative description of a second creature based on the second product description;defining at least one characteristic of the second creature distinct from the second narrative description;generating an image of the second creature based on the second narrative description; andstoring, in the data store, a second data set defining the second creature, the second data set including;the at least one characteristic of the second creature; andthe image of the second creature.

18. The method of claim 17 further comprising:providing a first implementation of a user interface associated with the first creature at a first user interface device and a second implementation of the user interface associated with the second creature at a second user interface device;initiating, at one of the first user interface device and the second user interface device, a battle between the first creature defined in the first data set and the second creature defined in the second data set;applying an in-game battle engine to define a winner of the battle based at least partially on the at least one characteristic of the first creature and the at least one characteristic of the second creature; andAttorney Docket: WRCD 15356WOindicating the winner of the battle at each of the first user interface device and the second user interface device.

19. The method of claim 18 further comprising providing an in-game reward to the winner of the battle, wherein the in-game reward modifies the at least one characteristic of the corresponding creature or is provided in the form of in-game currency.

20. The method of claim 1 further comprising providing a user interface associated with the video game at a user interface device wherein the first creature is usable as a playable character, wherein the first product identifier is machine readable and wherein acquiring the first product identifier is by scanning the first product identifier at the user interface device.

21. The method of claim 20 wherein the first product identifier is a code for looking up product information and does not encode product information, and wherein the first product description is retrieved from a database based on the first product identifier.

22. The method of claim 1 further comprising printing the first data set on a card for use in a card based game.

23. The method of claim 1 further comprising printing the image of the first creature on a physical object.

24. A system for implementing a video game comprising:a data store that stores virtual character data for virtual characters playable in a video game;a computer readable memory containing instructions for implementing the video game;a first user interface device; anda computing system in communication with the data store and the computer readable memory configured to execute computer-readable instructions in order to;scan, at the first user interface device, a machine readable first product identifier associated with a first physical object;Attorney Docket: WRCD 15356WOacquire a first product description based on the scanned first product identifier;generate a first narrative description of a first creature based on the first product description;define at least one characteristic of the first creature distinct from the first narrative description;generate an image of the first creature based on the first narrative description; andstore, at the data store, a first data set defining the first creature, the first data set including:the at least one characteristic of the first creature; andthe image of the first creature.

25. The system of claim 24 further comprising a second user interface device, wherein the computing system is further configured to execute the computer-readable instructions in order to:scan, at the second user interface device, a machine readable second product identifier associated with a second physical object;acquire a second product description based on the scanned second product identifier;generate a second narrative description of a second creature based on the second product description;define at least one characteristic of the second creature distinct from the second narrative description;generate an image of the second creature based on the second narrative description; andstore, at the data store, a second data set defining the second creature, the second data set including:the at least one characteristic of the second creature; andAttorney Docket: WRCD 15356WOthe image of the second creature.

26. The system of claim 25 wherein the computing system is further configured to execute the computer-readable instructions in order to provide a first implementation of a user interface associated with the first creature at the first user interface device and a second implementation of the user interface associated with the second creature at the second user interface device, and to provide a battle system by which a battle between the first creature and the second creature is initiated from one of the first and second user interface devices.

Images