20 results about "Battlefield" patented technology

The present application relates to the technical field of game artificial intelligence, and particularly relates to a global deployment decision method and device for virtual objects, equipment and medium, the method specifically comprises: determining a first virtual object set, establishing a battle database for each first virtual object in the first virtual object set, and giving a second virtual object the permission to access the battle database of each first virtual object; based on the battle database, the second virtual object respectively acquires the role data of each first virtual object, and then according to the battlefield element of the current battlefield and the role data of each first virtual object, determines a third virtual object set and the deployment arrangement of each third virtual object in the current battlefield in the third virtual object set. The present application makes global decision judgment such as pre-battle deployment, in-battle analysis and post-battle summary, so that each virtual object on the field can make the optimal action.

The invention discloses a gear transmission type historical war deduction sand table control mechanism, and relates to the technical field of sand table control, the gear transmission type historical war deduction sand table control mechanism comprises a sand table mounting seat, control mechanisms, models, a glass plate and a projector, the top of the sand table mounting seat is slidably connected with twelve groups of control mechanisms, and the control mechanisms are arranged; a tooth-shaped structure is used for accurately transmitting power, the motion direction and speed of the model are controlled, stable and accurate movement and rotation of the model are guaranteed, and the reliability and simulation precision of deduction sand table operation are improved; a flag mechanism is arranged, and the flag state is rapidly switched during position attribution, tactical deployment change and attack and defense situation conversion, so that a deducer can clearly control the battlefield dynamic state, the deduction efficiency and the battlefield situation visualization degree are improved, and accurate and smooth deduction is guaranteed; the lifting mechanism is arranged, three-dimensional dynamic simulation of topographic relief and unit height is achieved through upward or downward movement of the model, plane deduction is expanded into three-dimensional battlefield reduction, and the authenticity and visualization degree of tactical deployment are improved.

The application discloses an event extraction method and system fusing a graph attention network and a QA extraction paradigm, and aims at historical combat texts including military events. Based on a graph attention network and a classification mechanism, the historical combat texts are preprocessed, trigger words are recognized, and event argument role extraction is carried out, so that the text is processed, the accuracy of event extraction is improved, and the extraction efficiency of key information is improved and the time of command decision is shortened in a complex and changeable battlefield environment.

The invention provides an automatic situation plotting method and device and electronic equipment, and the method comprises the steps: carrying out the key information extraction of an initial combat plan text based on a large language model, obtaining the key combat information in the initial combat plan text, and carrying out the retrieval in a military mark library based on the key combat information, obtaining an initial military mark corresponding to the key battle information, and plotting the initial military mark in a military map to obtain an initial situation map of a battlefield; and performing key information extraction on the received battlefield real-time data, and updating the initial situation map based on the extracted real-time key information to obtain a real-time situation map of the battlefield. Based on the combination of the large language model and the military standard library, the whole process automation from the battle plan to the real-time situation icon drawing update is realized, the battlefield situation awareness efficiency and accuracy are obviously improved, and powerful support is provided for command decision making.

The application discloses a kind of based on key event detection's wargaming process key battle method mining method and device, comprising: the multi-resolution situation feature abstraction of the wargaming data collected, obtain the battlefield situation feature set of combat unit under uniform dimension;Known key event in wargaming data is extracted based on battlefield situation feature set using weak supervision self-training method, and specific key event set is obtained;Based on battlefield situation feature set and specific key event set, new key event in wargaming data is extracted using new key event identification method based on deep hidden layer feature, and new key event set is obtained by labeling new key event;Each key event in specific key event set and new key event set is combined according to time sequence relationship, forms multiple battle method set, completes key battle method mining.The present application improves the timeliness and accuracy of key battle method mining.

The present application belongs to the field of military simulation technology, and specifically discloses a battle example data conversion method, system and program product for war game deduction, which realizes the automatic conversion from multi-source heterogeneous battle example data to standardized and executable war game deduction plan through data preprocessing and element sequence extraction on the multi-source heterogeneous battle example data, and then script generation using the extracted element sequence, thereby improving the battle example data conversion efficiency and the intelligent level of war game deduction; through the fusion and conflict resolution of multi-source elements, high-precision element extraction can be realized, the accuracy of element extraction is ensured, and the battle game deduction example data conversion demand of complex battlefield scenes can be supported; and through the automatic battle example data conversion processing, manual intervention can be reduced, the efficiency and quality of battle example data conversion are improved, and the present application is suitable for large-scale battle example library.

The invention discloses an intelligent judgment decision-making system in red-blue confrontation training, and the system comprises a multi-source battlefield data collection module which is used for obtaining the military strength states of red and blue parties and a battle event in real time, and generating real-time battle situation data; the intelligent behavior simulation and confrontation judgment module is used for driving a blue military target to act based on the real-time battle situation data and outputting a hit part and damage grade judgment result; the multi-dimensional battlefield evaluation and redisk analysis module is used for carrying out battlefield damage statistics and capability evaluation and supporting two / three-dimensional situation playback and key event reproduction; and the closed-loop feedback and guidance intervention module is used for dynamically adjusting the confrontation intensity according to the evaluation result and the training target, and realizing real-time intervention of the blue army action strategy and closed-loop regulation of the training process. According to the embodiment of the invention, objectization, intelligentization and process of red-blue confrontation training judgment can be realized, and the fidelity, the evaluation accuracy and the group training efficiency of military training are improved.

The invention discloses a battlefield situation visualization method and system. The method comprises the steps that a reconnaissance front end analyzes and plans tasks of the reconnaissance front end according to actual conditions of a battlefield before the reconnaissance front end takes off; in the flying process of the reconnaissance front end, modeling is conducted on battlefield conditions and situation targets in real time, and target coordinates are automatically recognized and marked; after the reconnaissance front end completes the reconnaissance task of the whole battlefield, the target property, position and state of the whole battlefield are marked on an electronic map, the threat degree is calculated, and an attack list or a firepower plan is edited; after a battlefield reconnaissance task is completed by the reconnaissance front end for multiple times, target coordinates, threat degree information and target movement tracks of a battlefield in different time periods are marked on an electronic map, and situation evolution is displayed according to a time axis; the method has the advantages that global, associated and dynamic perception of the battlefield situation is realized, so that rapid and accurate decision information can be provided for a commander.

This invention relates to a visualization control method and system for the aggregation and deaggregation of combat formations, belonging to the field of data visualization technology. The method includes: establishing entity triples based on the entities within the combat formation and the entity relationships between them; constructing a knowledge graph; and storing the constructed knowledge graph in a combat formation graph database; establishing rules for switching between aggregation and deaggregation displays based on the map scale; and determining whether to perform aggregation and deaggregation display switching for combat formations in the battlefield situation; and performing aggregation or deaggregation display based on the results of the aggregation and deaggregation display switching determination. The method and system provided in this application can switch between aggregation and deaggregation displays for combat formations in the battlefield situation according to user needs; aggregation display can reduce the overlapping and chaotic phenomena in situation display, accelerate situation recognition speed, and improve display smoothness; and during deaggregation display, combat formations can be displayed accordingly based on user needs.

The invention discloses a computer war game combat system, which comprises an army module, a battlefield module and a combat settlement module, and is characterized in that the army module comprises a plurality of sub-units, each sub-unit is an independent single weapon, and each sub-unit is composed of a plurality of personnel; the battlefield module is used for calculating the width of a battlefield according to the attacked plot and determining the position of the battlefield and the number of receivable troops; the combat settlement module calculates damage according to a damage formula every day, carries out damage judgment, calculates casualties and organization degrees according to results, and updates troop states. The battlefield width, the army combat width and the inter-army width are set, the space limitation and combat conditions of the army on the battlefield are simulated more truly, and the situation that a user obtains improper advantages through an unreasonable army compilation mode is avoided; and meanwhile, the combat settlement module adopts a new calculation formula for calculation according to the attributes of different weapon types, so that the strategy and authenticity of the game are increased, and the user can better formulate strategies and tactics according to the characteristics of the different weapon types.

This invention discloses a multi-level AI architecture for wargaming, including a computational engine for acquiring battlefield information and transmitting it to a combat intent layer, a task allocation layer, and an operator action layer; receiving and executing actual operator action instructions output by the operator action layer; the battlefield includes the combatant and the enemy; the combat intent layer is used to determine the current battlefield situation based on battlefield information and generate tactical intentions; the task allocation layer is used to generate an operator task list based on battlefield information and tactical intentions; the operator action layer generates actual operator action instructions based on battlefield information and the operator task list; this improves the accuracy of wargaming while reducing the complexity and time consumption of decision-making calculations.

The application discloses a sea battle reasoning method based on mixed granularity events, which comprises the following steps: determining important terms and concept words in the field and application range of ontology according to knowledge data of a battle knowledge base; establishing a vocabulary list according to the important terms and concept words; defining the ontology class and the hierarchy of the class, determining the parent-child relationship and parallel relationship between the classes according to the vocabulary list; defining the attributes and attribute constraints of the class, and obtaining a sea battlefield combat event ontology model; implementing instantiation on the sea battlefield mixed granularity combat information through the sea battlefield combat event ontology model, obtaining a plurality of sea battlefield combat events and storing the events in a battle rule knowledge base; reasoning the obtained sea battlefield combat events according to a BN reasoning engine module, and obtaining a sea battlefield combat event to be executed at the next moment. The method is convenient for describing the key events, semantic elements and the relationship between the events of the sea battlefield combat, and greatly improves the efficiency of the deduction of the sea battlefield task through the analysis of the military field knowledge and the decision-making knowledge of the commander.

Provided is a game system 1 that is a system for a game, the system having a plurality of information processing devices 10, the game including a story game and a battle game, battle presentation information with respect to terminal devices 10 of battle players of a battle in the battle game being calculated by using production information for the story game, and the battle being observable at a terminal device 10 of a battle-observation player, at least one of the information processing devices 10 including a battle-observation-presentation-information calculation unit 52 that calculates battle-observation presentation information with respect to the terminal device 10 of the battle-observation player of the battle on the basis of production information based on a progress level of the battle-observation player in the story game and input information related to the battle.

The invention discloses a multi-modal perception optimization method and system based on domain knowledge enhancement. The method comprises the following steps: acquiring multi-modal battlefield sensing data, performing space-time synchronization and military feature extraction, and constructing a standardized battlefield state vector; the method comprises the following steps: constructing a three-layer military domain knowledge constraint model of a battlefield structure geometric knowledge model, a combat tactical rule knowledge model and a weapon equipment physical motion consistency knowledge model, and outputting a battlefield structure geometric constraint term, a combat tactical rule constraint term and a weapon equipment physical motion consistency constraint term, and respectively evaluating the consistency of geometric structure features in the battlefield state vector and a battlefield prior structure, target state transition in the battlefield state vector, combat tactical logic and the like. According to the method, through a three-layer domain knowledge constraint and knowledge trigger type compensation mechanism, perception errors are effectively inhibited, optimization failure caused by data missing is avoided, and perception stability and reliability are remarkably improved.

A method of training an artificial intelligence (AI) system, comprising: (a) displaying an initial version of a battlefield environment visualization showing at least one asset and two or more threats; (b) receiving from a user a threat level for each of the two or more threats; (c) displaying a subsequent version of the battlefield environment visualization in which the two or more threats have a subsequent geospatial relationship with respect to the at least one asset; (d) receiving from the user an updated threat level for at least one of the two or more threats for the subsequent version of the battlefield environment visualization; and (e) reiterating steps c and d at least once to create a training data set of updated threat levels for changing subsequent geospatial relationships of threats relative to the at least one asset.

The application discloses a ground combat victory rate prediction method and system based on deep learning, and relates to the technical field of battle prediction. The method comprises the following steps: acquiring time series of battlefield situation data of two parties in a ground combat scene; inputting the time series of the battlefield situation data into a ground combat scene real-time victory rate prediction model to obtain a victory rate prediction value of the two parties; and the ground combat scene real-time victory rate prediction model is obtained by training a double-layer LSTM neural network by using a combat data set. The application improves the efficiency and accuracy of victory rate prediction.

The application discloses a kind of wargaming system's algorithm test case generation method, medium and electronic equipment, method includes: constructing combat entity behavior algorithm test task library;Respectively construct the ontology model of battlefield scene, combat task and combat demand;Generation combat task logic diagram;Based on combat task logic diagram and combat entity behavior algorithm test task library, through battlefield scene each element combination rule generates combat basic situation;According to the parameter range and correlation of state space variable defined in the ontology model of battlefield scene, representative discrete values are selected for combination, to generate test cases covering typical scenarios;According to the internal correlation of the behavior algorithm of test case, scene and task, establish the mapping rule of test case and wargaming system, adaptively access different resolution wargaming system.According to the method of the application, the comprehensive capability test of algorithm can be realized, and is high in reliability, high in efficiency, high in coverage.

The invention provides a battlefield entity trajectory real-time clustering method and system based on hexagonal lattice Hash, and relates to the technical field of computer war game deduction and military training simulation.The method comprises the steps that a continuous battlefield space is discretized into a hexagonal lattice network, trajectory point mapping is conducted in combination with the hexagonal lattice network and Hash mapping to obtain hexagonal lattice Hash buckets, and the hexagonal lattice Hash buckets are clustered; each hexagonal lattice hash bucket stores entity track points with the same hash value; incremental clustering is carried out based on the hexagonal lattice Hash bucket, and a clustering cluster is obtained through core lattice identification and cluster expansion; tactical logic verification is carried out on the clustering clusters, and compliance clusters and abnormal clusters are marked through rule matching and space-time logic verification; and performing real-time rendering based on the compliance cluster and the abnormal cluster to obtain a battlefield entity trajectory visualization result. According to the method, the problems of parameter drift and computing resource overload caused by data accumulation and no consideration of tactical causal constraints in the prior art are solved.

This invention provides a heterogeneous wargame simulation decision-making method, apparatus, device, and storage medium based on LLM-MARL collaborative driving. By extracting features and quantifying military terminology from the battlefield situation, and generating structured situation text according to a protocol template, the LLM strategic planner outputs a tactical intent vector, achieving high-level semantic mapping to a tensor space. Using the tactical intent vector and local agent observations as query and key-value sources respectively, an intent-guided feature is generated via a cross-attention network, driving the policy network to output actions, thus guiding the underlying actions based on strategic intent. The actions and observation trajectories are mapped to a shared semantic space, and joint training combining consistency loss and environmental rewards constrains the convergence of tactical trajectories towards strategic intent. Furthermore, reflective feedback is generated based on execution deviation, driving the LLM to update the tactical intent vector, forming a two-way collaborative optimization closed loop.