Computing apparatus, system and method for balancing forecast signals from remote terminals

Description

1 / 22 APPARATUS, SYSTEM AND COMPUTING METHOD FOR BALANCING PREDICTION SIGNALS FROM REMOTE TERMINALS REFERENCE TO RELATED PATENT APPLICATIONS

[0001] This patent application claims the benefit of U.S. Provisional Patent Application No. 63 / 460457, filed April 19, 2023, entitled “COMPUTING APPARATUS, SYSTEM AND METHOD FOR BALANCING PREDICTION SIGNALS FROM REMOTE TERMINALS”, the full content of which is incorporated herein by reference. FIELD

[0002] The present disclosure relates generally to computer systems that manage signals through communication networks and, more particularly, to the balancing of resource utilization. FUNDAMENTALS

[0003] Computing devices and communication systems are commonly employed to facilitate networked software interactions involving signals. Significant engineering resources may be expended in the design and implementation of a hardware platform that provides a particular experience to those accessing the platform through remote terminals. However, remote terminals may exhibit a variable signal flow that reflects user behavior, which can further influence the utilization of the hardware platform. Thus, computing resources of certain platforms are underutilized and / or unbalanced, resulting in wasted processor, memory, and communication resources. SUMMARY

[0004] One aspect of the specification provides an interactive platform that includes a processor and memory, the processor configured to: define a target resource utilization range of one or more processor, memory and / or bandwidth utilizations of the platform; launch an interactive application Petition 870250113113, dated 09 / 12 / 2025, page 9 / 36 2 / 22 on the platform; determine a plurality of participating accounts associated with electronic devices that connect to the platform via a network; receive forecast signals for an application outcome from at least a portion of the participating accounts; execute an application step; determine which participating accounts generated forecast signals; allocate a first portion of a collective account to a value storage unit associated with one of the participating accounts associated with an accurate forecast; allocate a second portion of the collective account among one or more value storage units associated with the other participating accounts based on a number of forecast signals received from the other participating accounts; wherein the second portion is adjusted to bring the total number of forecast signals within the target resource utilization range during subsequent steps.

[0005] One aspect of the specification provides a system comprising a plurality of platforms hosting the interactive application as set forth above. The target utilization range includes one or more processor, memory, and bandwidth utilizations from each platform. The target utilization range includes a substantial balance of processor, memory, and bandwidth utilization on each platform.

[0006] One aspect of the specification provides an interactive platform where the target range is between approximately 20% and approximately 80% of processor utilization.

[0007] One aspect of the specification provides an interactive platform where the target range is between approximately 30% and approximately 70% of processor utilization.

[0008] One aspect of the specification provides an interactive platform where the target range is between approximately 40% and approximately 60% of processor utilization.

[0009] One aspect of the specification provides a platform Petition 870250113113, dated 09 / 12 / 2025, page 10 / 36 3 / 22 interactive where the target range is between approximately 45% and approximately 55% of processor utilization.

[0010] One aspect of the specification provides an interactive platform where the target range is approximately 50% of processor utilization.

[0011] One aspect of the specification provides an interactive platform where the target range is between approximately 25% and approximately 75% of memory utilization.

[0012] One aspect of the specification provides an interactive platform where the target range is between approximately 35% and approximately 75% of memory utilization.

[0013] One aspect of the specification provides an interactive platform where the target range is between approximately 40% and approximately 60% of memory utilization.

[0014] One aspect of the specification provides an interactive platform where the target range is between approximately 45% and approximately 55% of memory usage.

[0015] One aspect of the specification provides an interactive platform where the target range is approximately 50% of memory usage.

[0016] One aspect of the specification provides for between approximately 25% and approximately 75% of the network connection bandwidth usage to the platform.

[0017] One aspect of the specification provides an interactive platform where the target range is between approximately 35% and approximately 75% of the network connection bandwidth usage to the platform.

[0018] One aspect of the specification provides an interactive platform where the target range is between approximately 40% and approximately 60% of the network connection bandwidth usage to the platform.

[0019] One aspect of the specification provides an interactive platform where the target range is approximately Petition 870250113113, dated 09 / 12 / 2025, page 11 / 36 4 / 22 45% and approximately 55% of the network connection bandwidth is used on the platform.

[0020] One aspect of the specification provides an interactive platform where the target range is between approximately 50% of the network connection bandwidth utilization to the platform.

[0021] One aspect of the specification provides a platform that includes a processor configured to: initiate an electronic game on the platform; determine a plurality of participating accounts associated with electronic devices that connect to the platform via a network; receive prediction signals for a game outcome from the participating accounts; execute a game step of the electronic game; determine which participating accounts generated prediction signals; allocate a first portion of a collective monetary account to a monetary account associated with one of the participating accounts associated with an accurate prediction; allocate a second portion of the collective monetary account among one or more of the other participating accounts based on a number of prediction signals received from the other participating accounts; wherein the second portion is adjusted to bring the total number of prediction signals into a target range during the subsequent initiation of the electronic game.

[0022] One aspect of the specification provides a gaming platform where the electronic game is poker and the game stage includes a plurality of poker hands; the collective monetary account represents a pot; the first portion represents the winnings; and the second portion represents rakeback. BRIEF DESCRIPTION OF THE FIGURES

[0023] Figure 1 is a schematic diagram of a system for balancing forecast signals.

[0024] Figure 2 is a block diagram of illustrative internal components of the load balancing mechanism of Petition 870250113113, dated 09 / 12 / 2025, page 12 / 36 5 / 22 Figure 1.

[0025] Figure 3 shows a flowchart describing a method for balancing forecast signals.

[0026] Figure 4 shows the system from Figure 1 executing certain blocks of the method from Figure 3.

[0027] Figure 5 shows another flowchart that describes another method for balancing forecast signals.

[0028] Figure 6 shows an electronic game table according to another modality. DETAILED DESCRIPTION

[001] Figure 1 shows a system for balancing forecast signals generally indicated at 100. The 100 system comprises a plurality of platforms 104-1, 104-2 ... 104-n. (Collectively, platforms 104-1, 104-2 ... 104-n are referred to as platforms 104 and, generically, as platform 104. This nomenclature is used elsewhere in this document.) In system 100, platforms 104 connect to a network 108 such as the Internet. The network 108 interconnects the gaming platforms 104 with a plurality of terminals 116 and a load balancing mechanism 120. As will be discussed later, the load balancing mechanism 120 performs various processing functions for system 100.

[002] Platforms 104 may be based on any current or future interactive application servers. In a non-limiting example, platforms 104 may be game servers for online game interactions between users 124 operating terminals 116. Terminals 116 may be any type of human-machine interface for interacting with platforms 104. For example, terminals 116 may include traditional laptops, desktop computers, mobile phones, tablet computers, and any other device that can be used to send and receive communications across the network 108 and its various nodes that complement the Petition 870250113113, dated 09 / 12 / 2025, page 13 / 36 6 / 22 input and output hardware devices associated with a given terminal 116. Terminals 116 that may include virtual or augmented reality equipment complementary to virtual or augmented reality environments or metaverses that may be offered on gaming platforms 104 are contemplated. Terminals 116 may be operated by different users 124 who are associated with a respective identifier object 128 that uniquely identifies a given user 124 accessing a given terminal 116 in the system 100. A unit of value storage in the form of a monetary account 132 is also associated with each identifier object 128.

[003] In a current exemplary embodiment, gaming platforms 104 may be based on media platforms or central servers that function to provide gaming interactions between different users 124 who have an account associated with their identifier object 128 on those platforms 104. Gaming interactions are not particularly limited, but may include any form of game involving a plurality of users 124 that combines skill and luck and includes rounds of predictions (bets) made by users 124 as to the outcome of the game. Each prediction is accompanied by an amount represented by a currency transferred from the monetary account 132 associated with the identifier object 128. As part of the game, predictions may be optional, however, continued participation in the game may depend on providing a prediction and a minimum amount of currency.The nature of the currency may vary depending on local laws and regulations governing the operation of the 100 system, such as currencies that represent in-game value or others that are equivalent to hard currency; this does not affect the present specification in any way.

[004] During the game, the coin from each round of predictions is pooled into a collective account 136 (for example, in online poker, the pot; this may be referred to by other colloquialisms, Petition 870250113113, dated 09 / 12 / 2025, page 14 / 36 7 / 22 depending on the game) referring to the gaming platform 104 that hosts the relevant game. As soon as a result matching the predictions becomes known, usually at the end of a game, a user 124 who made accurate predictions receives a portion of the collective account 136, which is transferred to the monetary account 132 associated with that user 124. (e.g., in online poker, the winnings; this may be referred to by other colloquialisms depending on the game). The remainder of the collective account 136 is transferred to the gaming platform's monetary account 140 (e.g., in online poker, the pot rake; this may be referred to by other colloquialisms depending on the game). An additional portion of the collective account 136 is allocated to a loyalty account 144 (e.g., in online poker, rakeback; this may be referred to by any other colloquialisms depending on the game).

[005] Portions of the currency in the loyalty account 144 are then distributed among the accounts 132 of users 124 who made inaccurate predictions, according to an algorithm implemented by the load balancing mechanism 120. The algorithm configures the load balancing mechanism 120 to control the gaming platforms 104 in order to maximize the utilization of the computational resources of each platform 104. A portion of the algorithm, in one embodiment, may be based on the number of times a user 124 made a prediction, even if those predictions were incorrect. The algorithms, prediction numbers, collective account values ​​136, platform account values ​​140, and loyalty account values ​​144, and related threshold levels are constantly monitored by the load balancing mechanism 120, making adjustments to seek to maximize the utilization of the computational resources of platforms 104 within the system 100.

[006] A current illustrative example of a 104 gaming platform is online poker, but any online game according to the Petition 870250113113, dated 09 / 12 / 2025, p. 15 / 36 8 / 22 The general structure above is contemplated. In the context of online poker, the collective account 136 can be colloquially referred to as the pot; the portion of the collective account 136 that is transferred to the monetary account 132 associated with a user 124 who made accurate predictions in winning the poker hand can be colloquially referred to as winnings; while the distribution of the loyalty account 144 can be referred to as rakeback. The platform's monetary account 140 can be colloquially referred to as the pot rake; the nature of gaming platforms 104 is therefore not particularly limited. Very generally, platforms 104 provide a means for users 124 to play online games with each other through terminals 116, while the load balancing mechanism 120 makes adjustments to maximize the utilization of the platforms 104.Thus, in variations, the present specification can be applied to a multiplayer game, such as a modified version of the Battle Royale mode in a game like Fortnite, where, during predefined moments, players are encouraged to make a prediction about the probability of them, or their team, emerging victorious.

[007] At this point, it should be clear and understood that the nodes in the system 100 are massively scalable, to accommodate a large number of users 124, terminals 116 and gaming platforms 104. Thus, the terminals 116 are based on any suitable client computing platforms (with examples mentioned above) operated by users 124 who may be interested in participating in a game with other users 124 on one or more gaming platforms 104. Each terminal 116 and its user 124 are thus associated with a user identifier object 128 and an electronic monetary account 132.

[008] A person skilled in the art should recognize that the form of an identifier object 128 is not particularly limited and, in a simple exemplary embodiment, may be a sequence Petition 870250113113, dated 09 / 12 / 2025, page 16 / 36 9 / 22 alphanumeric that is completely unique in relation to other identifier objects in the system 100. Identifier objects can also be more complex, as they can be combinations of account credentials (e.g., username, password, two-factor authentication token, etc.) that uniquely identify a given user 124. The identifier objects themselves can also be indexes that point to other identifier objects, such as accounts. The salient point is that they are uniquely identifiable within the system 100 in association with what they represent and can be associated with accounts for each user 124 on one or more platforms 104.

[009] Having described an overview of system 100, it is useful to comment on the hardware infrastructure of system 100. Figure 2 shows a schematic diagram of a non-limiting example of internal components of the load balancing mechanism 120.

[0010] In this example, the load balancing mechanism 120 includes at least one input device 204. The input from device 204 is received by a processor 208 which, in turn, controls an output device 212. The input device 204 can be a traditional keyboard and / or mouse to provide physical input. Similarly, the output device 212 can be a screen. In variants, additional devices and / or other input devices 204 or output devices 212 are contemplated or may be omitted entirely, as the context requires.

[0011] The 208 processor can be implemented as a plurality of processors or one or more multi-core processors. The 208 processor can be configured to execute different programming instructions in response to input received through one or more input devices 204 and to control one or more output devices 212 to generate output on those devices. Petition 870250113113, dated 09 / 12 / 2025, page 17 / 36 10 / 22

[0012] To fulfill its programming functions, the 208 processor is configured to communicate with one or more memory units, including non-volatile memory 216 and volatile memory 220. Non-volatile memory 216 may be based on any persistent memory technology, such as an Electronically Erasable Programmable Read-Only Memory (“EEPROM”), flash memory, solid-state hard disk (SSD), other types of hard disk drives, or combinations thereof. Non-volatile memory 216 may also be described as a non-transient, computer-readable medium. Furthermore, more than one type of non-volatile memory 216 may be provided.

[0013] Volatile memory 220 is based on any random access memory (RAM) technology. For example, volatile memory 220 may be based on Double Data Rate (DDR) Synchronous Dynamic Random Access Memory (SDRAM). Other types of volatile memory 220 are contemplated.

[0014] Processor 208 also connects to network 108 via network interface 232. Network interface 232 can also be used to connect another computing device that has an input and output device, thus eliminating the need for input device 204 and / or output device 212.

[0015] Programming instructions in the form of applications 224 are normally maintained persistently in non-volatile memory 216 and used by the processor 208, which reads them from and writes them to volatile memory 220 during the execution of the applications 224. Several methods discussed in this document can be coded as one or more applications 224. One or more tables or databases 228 are maintained in non-volatile memory 216 for use by the applications 224.

[0016] The load balancing mechanism infrastructure 120, or a variant thereof, can be used to implement any of the computing nodes in system 100, Petition 870250113113, dated 09 / 12 / 2025, page 18 / 36 11 / 22 including platforms 104 and reservation mechanisms 112. Furthermore, the load balancing mechanism 120, platforms 104, and reservation mechanisms 112 can also be implemented as virtual machines and / or with mirror images. The load balancing mechanism 120 can also be incorporated directly into the platforms 104, thus eliminating the need for a central load balancing mechanism 120. Similarly, multiple load balancing mechanisms 120 can be provided, especially when the system 100 is scaled.

[0017] Furthermore, a person skilled in the art will recognize that the core elements of the processor 208, input device 204, output device 212, non-volatile memory 216, volatile memory 220, and network interface 232, as described in relation to the server environment of the load balancing mechanism 120, have analogues in the different client machine formats, such as those that can be used to implement terminals 116. Again, terminals 116 can be based on computer workstations, laptops, tablet computers, mobile telephony devices, or the like.

[0018] Figure 3 shows a flowchart describing a method for resource load balancing generally indicated as 300. Method 300 can be implemented in system 100. Subject matter experts may choose to implement method 300 in system 100 or variants thereof, or with certain blocks omitted, executed in parallel, or in a different order than shown. Method 300 can therefore also be varied. However, for explanatory purposes, method 300 will be described in relation to its performance in system 100, with specific focus on treating method 300 as being executed on one or more platforms 104, but method 300 is also monitored by the load balancing mechanism 120.

[0019] Block 304 comprises the beginning of an electronic game. Petition 870250113113, dated 09 / 12 / 2025, page 19 / 36 12 / 22 As mentioned above, the nature of the game is not particularly limited, but for a current illustrative example, online poker will be discussed. According to the specific illustrative example in the 100 system, it will be assumed that the 104-1 gaming platform has an online poker game started. (For now, to simplify the explanation, the status of the remaining 104 gaming platforms, besides the 104-1 gaming platform, is ignored, but it will be understood that these can also be started and be part of the present teachings). Any online poker format can be used, such as Texas Hold'em, Omaha 4, Omaha 5, and Omaha 6.

[0020] Block 308 comprises the determination of participating accounts. To elaborate on our example, in block 308, platform 104-1 receives electronic signals from a plurality of terminals 116, including associated identifier objects 128, which indicate which users 124 will play or otherwise participate in the electronic game initiated in block 304. Figure 4 shows an illustration in which all users 124 shown in Figure 1 send signals 404 through their terminals 116 to the gaming platform 104-1 that include their account identifier objects 128, indicating their participation in the game initiated in block 304.

[0021] Block 312 comprises the reception of prediction signals. According to our specific example, each user 124 will control their terminal 116 to allocate a certain amount of currency to their account 132 and transfer that amount electronically to the collective account 136-1 of the platform 1041. The amount of currency can be predetermined by the game rules, as applied by the platform 104-1, such as ante or blind, through which user 124 makes a prediction of who will be the winning player.

[0022] Block 316 comprises the execution of the game phase. In general terms, block 316 covers the exchange of signals between the Petition 870250113113, dated 09 / 12 / 2025, page 20 / 36 13 / 22 platforms 104 and terminals 116 that implement the electronic interactions representing the actual game. In the online poker example, block 316 includes platform 104-1 distributing a virtual poker hand, according to the specific poker game being used. For example, if the online poker game is Texas Hold'em, then after the initial execution of block 316, each terminal 116, according to its account associated with a respective object 128, receives electronic representations of two private hole cards. (During subsequent cycles of method 300, in the case of the Texas Hold'em example, these steps are colloquially referred to as the flop, turn, and river steps).

[0023] Block 320 comprises the determination of which accounts had associated forecasts. According to this example, records are kept of which accounts associated with respective 128 objects participated in sending forecast signals in block 312. As will become clear in the later discussion, the specific accounts that participated in block 308 but do not participate in the forecast in block 312 may result in overall underutilization of platform 104-1, since the connection between a given client terminal 116 and platform 104-1 is active according to block 308, but signals are not being transferred through that connection in block 312. Consequently, processing and memory resources on platform 104-1 may be wasted.

[0024] Block 324 involves determining whether the game started in block 304 is complete. In the Texas Hold'em example, a determination is made not until the flop, turn, and river stages are completed, taking the method back to block 312, where additional prediction signals are received and the method continues as described previously, observing in block 320 which accounts made predictions in block 312.

[0025] A determination is made in block 324 when the Petition 870250113113, dated 09 / 12 / 2025, page 21 / 36 14 / 22 specific game is completed. In the example of Texas Hold'em, this can be referred to as the completion of a round or hand or deal.

[0026] Block 328 comprises the allocation of a predefined portion of the collective account to the monetary account associated with the identifier object that made the most accurate prediction(s) in block 312. In our example platform 104-1, assume that user 124-1 on terminal 116-1 made the most accurate prediction(s) by winning the Texas Hold'Em game, in which case a portion of the accumulated currency in collective account 136-1 (the winnings) is transferred to monetary account 132-1. As will be discussed later, the predefined portion may vary according to the load balancing aspects of system 100.

[0027] Block 332 involves determining which accounts that participated in Block 308 made forecasts, as counted in Block 320, exceeding a predefined limit. The predefined limit may be based on a number of times, as counted in Block 320. As will be discussed later, the predefined limit may vary according to the load balancing aspects of system 100.

[0028] Block 336 comprises the determination of a fidelity portion for inaccurate predictors that exceeded the limit in Block 332. To elaborate, a remaining portion of collective account 136-1 is transferred to fidelity account 144, and then portions of fidelity account 144 are nominally allocated among the identifier objects 128 associated with the users 124 who made inaccurate predictions and exceeded the limit of Block 332. Block 340 comprises the transfer of the allocations from Block 336 to the monetary accounts 132 pertaining to those users 124 who made inaccurate predictions.

[0029] At this point, it can be observed that, in method 300, allocations from loyalty account 144 are larger for participants in block 308 who also generate a certain number. Petition 870250113113, dated 09 / 12 / 2025, page 22 / 36 15 / 22 of the forecast signals in block 312, regardless of the accuracy of those forecasts.

[0030] Block 344 comprises the allocation of any remaining balance from the collective account to the platform's monetary account. In the specific example discussed above, this means that the portion of the collective account 136-1 that was not placed in the loyalty account 144-1 is transferred to the platform's monetary account 140-1. It should be understood that, although several variations of method 300 are contemplated, in particular, it can be noted that block 344 can be omitted entirely, insofar as the entirety of the currency in account 136-1 can be allocated in block 328 or block 340.

[0031] Figure 5 shows a flowchart describing a method for resource load balancing, usually indicated as 500. The 500 method can be implemented in the 100 system. Subject matter experts may choose to implement the 500 method in the 100 system or variants thereof, or with certain blocks omitted, executed in parallel, or in a different order than shown. The 500 method can therefore also be varied. However, for explanatory purposes, the 500 method will be described in relation to its performance in the 100 system, with specific focus on the handling of the 300 method as, for example, the 224-1 application maintained in the 120 load balancing mechanism and its interactions with the other nodes in the 100 system.

[0032] When considering method 500 in relation to system 100, load balancing mechanism 120 performs a supervisory function over the remaining nodes in system 100 to adjust various thresholds and currency allocations to maximize the utilization of the central processing unit (CPU) or processor, memory consumption, and other performance metrics of the hardware used to implement platform 104. Mechanism 120, which has access to monitoring tools on each of the platforms, can report back to mechanism 120 the amount Petition 870250113113, dated 09 / 12 / 2025, page 23 / 36 16 / 22 of the computing resources being consumed by a given platform.

[0033] Thus, block 504 comprises the determination of a target utilization of platform resources. Block 504 is executed in engine 120 and defines desired target utilizations of platforms 104. For example, engine 120 can define a target range between approximately 20% and approximately 80% of CPU utilization for each platform 104. Engine 120 can define a target range between approximately 30% and approximately 70% of CPU utilization for each platform 104. Engine 120 can define a target range between approximately 40% and approximately 60% of CPU utilization for each platform 104. Engine 120 can define a target range between approximately 45% and approximately 55% of CPU utilization for each platform 104. Engine 120 can define a target range of approximately 50% of CPU utilization for each platform 104.

[0034] The 120 mechanism can define a target range between approximately 25% and approximately 75% of memory utilization for each 104 platform. The 120 mechanism can define a target range between approximately 35% and approximately 75% of memory utilization for each 104 platform. The 120 mechanism can define a target range between approximately 40% and approximately 60% of memory utilization for each 104 platform. The 120 mechanism can define a target range between approximately 45% and approximately 55% of memory utilization for each 104 platform. The 120 mechanism can define a target range of approximately 50% bandwidth utilization for each 104 platform.

[0035] Mechanism 120 can define target ranges for bandwidth consumption on network 108, between approximately 25% and approximately 75% of bandwidth usage for each platform 104. Mechanism 120 can define a target range Petition 870250113113, dated 09 / 12 / 2025, page 24 / 36 17 / 22 between approximately 35% and approximately 75% of bandwidth usage for each platform 104. Mechanism 120 can define a target range between approximately 40% and approximately 60% of bandwidth usage for each platform 104. Mechanism 120 can define a target range between approximately 45% and approximately 55% of bandwidth usage for each platform 104. Mechanism 120 can define a target range of approximately 50% of bandwidth usage for each platform 104.

[0036] Block 508 comprises the execution of a game instance. Method 400 is an example of a game instance that can be used to implement block 508, with the performance of method 400 being monitored by mechanism 120. However, as mentioned, method 400 is a modality, and other game instances that vary from method 400 can also be implemented in block 508. To reiterate, online poker is just one modality, and other online games are also contemplated. For the purposes of an illustrative explanation of method 500, however, reference will be made to method 400 and the previously mentioned example of Texas Hold'em.

[0037] Block 512 comprises the measurement of actual resource utilization. Thus, mechanism 120 will use resource monitoring tools maintained on each platform 104 to assess processor, memory, and bandwidth utilization. It is important to reiterate that other measurements of computational resources are contemplated in block 504 and block 512. Generally, the resource utilization measured in block 512 will be based on the metrics that established the target resource utilization from block 504.

[0038] Block 516 involves determining whether actual resource utilization, as measured in Block 512, is below a minimum target utilization defined in Block 504. Thus, for example, if CPU utilization is below a certain level. Petition 870250113113, dated 09 / 12 / 2025, page 25 / 36 18 / 22 target limit (such as the ranges and / or values ​​indicated above), then a yes determination is made and block 520 is invoked.

[0039] Block 520 comprises the adjustment of limit aspects associated with the game instance invoked in block 508. Continuing with the example of method 400 and platform 104-1, block 520 may comprise increasing the fidelity portion determined in block 336 and / or increasing the platform account portion in block 344 and / or decreasing the prediction limit in block 332. In this way, during the execution of block 328, block 332, block 336, and block 340, additional fidelity signals may be returned to terminals 116-1, thus increasing the overall utilization of computational resources and bandwidth by platform 104-1. Additionally, if one of the 124 users demonstrates a high level of repeated ability to make accurate predictions, the 520 block helps mitigate the effects of the remaining 124 users becoming aware of this pattern and thus refusing to participate in providing their own prediction signals.In other words, if a particular player demonstrates a dominant skill level compared to other players, the system 100 adjusts its behavior by increasing the loyalty reward to other players, thus maintaining, on average, higher levels in all monetary accounts 132 and encouraging all users 124 to participate more equitably in the gaming platform 104, thus providing an opportunity to keep the gaming platforms 104 operating within a desired level of computational resource utilization, as defined in block 508.

[0040] When implemented in online poker algorithms for the 520 block, it can be based on the colloquial Voluntary Put Money in Pot (VPIP), which tracks the percentage of hands in which a given player voluntarily puts money into the pot. Petition 870250113113, dated 09 / 12 / 2025, page 26 / 36 19 / 22 pot (i.e., generates a prediction signal on block 312) preflop. VPIP raises when a player could fold but instead commits money to the pot preflop. This includes limping (just paying the big blind), calling, and raising.

[0041] VPIP, or Voluntarily Put Money in Pot, is a poker statistic used to measure a player's overall aggressiveness and is commonly used in the context of online poker. VPIP is expressed as a percentage and represents how often a player puts money into the pot preflop, whether by calling, raising, or completing the blinds.

[0042] The VPIP percentage is calculated by dividing the number of times a player voluntarily puts money into the pot by the total number of hands played. A higher VPIP percentage indicates a looser and more aggressive playing style, while a lower VPIP percentage signifies a more restrained and passive approach.

[0043] For example, a player with a VPIP of 10% would voluntarily contribute to the pot in only 10% of the hands they play, indicating a very restricted and selective playing style. On the other hand, a player with a VPIP of 40% would contribute to the pot in 40% of the hands they play, suggesting a much looser and more aggressive style.

[0044] VPIP is often used in combination with other poker statistics, such as PFR (Preflop Raise percentage) and AF (Aggression Factor), to help players analyze their opponents' playing styles and make better decisions at the table.

[0045] These aspects of online poker can be used to make adjustments to the 520 block in order to induce the 100 system to achieve target resource utilization.

[0046] Returning to block 516, if, on the other hand, the use Petition 870250113113, dated 09 / 12 / 2025, p. 27 / 36 If the actual utilization of block 512 is greater than a minimum target utilization, then no determination is made in block 516 and method 500 proceeds to block 524. Block 524 comprises determining whether the actual utilization of block 512 exceeds a maximum target utilization, as defined in block 504.

[0047] A yes determination in block 524 leads to block 528, which performs an opposite set of adjustments to block 520, cooling down excessive predictions that could overload the computational resources of platform 104. Block 528 is the inverse of block 520. In other words, the amount of the fidelity portion can be decreased and / or the amount of the platform account and / or the limit on the number of predictions in block 332 can be increased, thus cooling down the number of prediction signals sent in block 312 and thus decreasing the overall use of the computational resources of platform 104.

[0048] A "no" determination in block 524 leads to block 532, meaning that the actual resource utilization in block 512 is within the target range in block 504. Block 532 is also reached from block 520 and block 528. Thus, block 532 comprises determining whether the target resource utilization itself should be adjusted. A "yes" determination leads back to block 504, while a "no" determination leads back to block 508, and the process repeats.

[0049] Block 532 may reach a yes determination when, for example, the lower target utilization limits are not consistently met by method 500, regardless of adjustments made in block 520. In this case, mechanism 120 may also merge different game platforms 104 into a single game platform 104. The opposite is also true, when upper target utilization limits are consistently exceeded and yet adjustments in block 528 do not sufficiently cool the signals between terminals 116 and the relevant platform 104. In this case, mechanism 120 may Petition 870250113113, dated 09 / 12 / 2025, pp. 28 / 36 21 / 22 automatically generate additional instances of 104 platforms. In this context, when 104 platforms are deployed as virtual machines, the number and processing resources of these virtual machines can be dynamically scaled up and down, in conjunction with the 500 method, to achieve overall system load balancing 100.

[0050] With reference now to Figure 6, an electronic gaming table according to another modality is generally indicated by 100a. Table 100a is a system 100 implemented as a Video Poker Machine or Electronic Poker Table. Table 100a includes elements similar to system 100, except followed by the suffix a. Table 100a thus includes a plurality of player terminals 116a that are analogous to terminal 116. Table 100a also includes a gaming mechanism 104a that performs the dealer functions of table 100a, as does platform 104, and a load balancing mechanism 120a that controls the mechanism 104a in order to promote the use of the gaming mechanism 104a by encouraging the increase of prediction signals from different player terminals 116a.

[0051] In view of the above, it is now evident that variations, combinations and subsets of the previous modalities are contemplated.

[0052] For example, in one variant, the platforms 104 may be virtual machines hosted by cloud service platforms, such as Amazon Web Services (AWS) or Google Cloud, or Microsoft Azure, which may be dynamically scaled up and down by the load balancing mechanism 120, with the load balancing mechanism 120 configured to achieve a desired level of utilization of computing resources, dynamically increasing or decreasing the virtual machine capacity of each platform 104 as the load balancing mechanism 120 influences increases or decreases in the number of participating endpoints 116 and associated numbers of Petition 870250113113, dated 09 / 12 / 2025, pages 29 / 36 22 / 22 predictions, using the teachings presented in this document.

[0053] A person skilled in the art will now understand that the teachings presented in this document can improve technological efficiency and the utilization of computational and communication resources throughout the system 100. Platforms 104 that do not benefit from the load balancing mechanism 120 may be chronically underutilized, especially when a particular user 124 has a pattern of making accurate predictions more frequently than others.

[0054] It should be recognized that features and aspects of the various examples given above may be combined in other examples that also fall within the scope of the present disclosure. Furthermore, the figures are not to scale and may be exaggerated in size and shape for illustrative purposes. Petition 870250113113, dated 09 / 12 / 2025, pages 30 / 36

Claims

1 / 3 CLAIMS 1. An interactive platform, characterized in that it includes a processor and memory, the processor configured to: define a target resource utilization range for one or more processor, memory, and / or bandwidth utilizations of the platform; initiate an interactive application on the platform; determine a plurality of participating accounts associated with electronic devices that connect to the platform via a network; receive prediction signals for an application outcome from at least a portion of the participating accounts; execute a phase of the application; determine which participating accounts generated prediction signals; allocate a first portion of a collective account to a value storage unit associated with one of the participating accounts associated with an accurate prediction;Allocate a second portion of the collective account among one or more units of value storage associated with the other participating accounts based on a number of forecast signals received from the other participating accounts; wherein the second portion is adjusted to bring the total number of signals within the target resource utilization range during subsequent phases.

2. System, characterized in that it comprises a plurality of platforms that host the interactive application as defined in claim 1; the target usage range including one or more processor, memory and bandwidth uses of each platform; the target usage range including a substantial balance of processor, memory and bandwidth use on each platform.

3. Interactive platform, according to claim 1, characterized in that the target range is between approximately 20% and approximately 80% of processor utilization.

4. Interactive platform, according to claim 1, characterized in that the target range is between approximately 30% and approximately 70% of processor utilization.

5. Interactive platform, according to claim 1, characterized in that the target range is between approximately 40% and approximately 60% of processor utilization.

6. Interactive platform, according to claim 1, characterized in that the target range is between approximately 45% and approximately 55% of processor utilization.

7. Interactive platform, according to claim 1, characterized in that the target range is approximately 50% of processor utilization.

8. Interactive platform, according to claim 1, characterized in that the target range is between approximately 25% and approximately 75% of memory utilization.

9. Interactive platform, according to claim 1, characterized in that the target range is between approximately 35% and approximately 75% of memory utilization.

10. Interactive platform, according to claim 1, characterized in that the target range is between approximately 40% and approximately 60% of memory utilization. Petition 870250095114, dated 10 / 17 / 2025, pp. 24 / 26 3 / 3 11. Interactive platform, according to claim 1, characterized in that the target range is between approximately 45% and approximately 55% of memory utilization.

12. Interactive platform, according to claim 1, characterized in that the target range is between approximately 25% and approximately 75% of the network connection bandwidth utilization to the platform.

13. Interactive platform, according to claim 1, characterized in that the target range is between approximately 35% and approximately 75% of the network connection bandwidth utilization to the platform.

14. Interactive platform, according to claim 1, characterized in that the target range is between approximately 40% and approximately 60% of the network connection bandwidth utilization to the platform.

15. Interactive platform, according to claim 1, characterized in that the target range is between approximately 45% and approximately 55% of the network connection bandwidth utilization to the platform.

16. Interactive platform, according to claim 1, characterized in that the target range is approximately 50% of the network connection bandwidth utilization to the platform. Petition 870250095114, dated 10 / 17 / 2025, pp. 25 / 26

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