Intelligent controllers for battlefield simulations

Realistic military simulations are needed for analysis, planning and training. Intelligent Agent Technology is a valuable software concept with the potential to be widely used in military simulation applications. They provide a powerful abstraction mechanism required for designing simulations of complex and dynamic battlefields. Their ability to model the tactical decision-making behaviour of battlefield entities gives an edge over many other software techniques because such a problem maps easily into agent based programming. This paper demonstrates the strength of this technology in modeling and simulating the battlefields. As a case study, the tactical and reactive behaviour of lower level battlefield entities such as tanks has been modeled using JACK TM Intelligent Agent Framework.

2008

Scripted Artificially Intelligent Basic Online Tactical Simulation Jesse D. Phillips+∗ Roger V. Hoang+∗ Joseph D. Mahsman+∗ Matthew R. Sgambati+∗ Xiaolu Zhang+ Sergiu M. Dascalu+Frederick C. Harris, Jr.+∗ Department of Computer Science and Engineering+ CAVCaM∗ ...

1991

Many theater-level combat simulation models were developed with a linear NATO-Warsaw Pact conflict in mind. Conversely, emerging AirLand Battle-Future doctrine stresses smaller forces on nonlinear battlefields. This paper describes how an existing theater-level model, the Concepts Evaluation Model (CEM), models many AirLand Battle and AirLand Battle-Future tenets with examples from Operation Desert Storm Campaign Analyses. THE METHODOLOGY MAY BE APPLIED TO any ground combat simulation model with properties similar to CEM (CEM is briefly described in Chapter 2). Recommended application would specifically include force on force theaterlevel combat models. MAJOR ASSUMPTIONS (1) AirLand Battle-Future (or AirLand Warfare or AirLand Operations) will be accepted by the US Army as its doctrine. (2) Most deterministic theater-level models are similar enough in their properties to allow application of some or all of the concepts embodied within this paper. (3) Computer simulations will continue to provide important insights into combat capabilities of forces. MAJOR LIMITATIONS (1) Applications and methodologies used within apply to CEM. Dissimilarities of other combat simulations may preclude adaptations of any or all of these insights. (2) The applications and methodologies described here were developed over an extremely short time period in order to provide timely, realistic simulations of critical combat contingency plans. Refinement or replacement of any or all of these methodologies after further research and development is possible. RESEARCH PAPER DATA Audience: Analysts familiar with the basic theories, assumptions, and challenges of combat simulation models. It is not intended for a lay audience.

SIMULATION, 2011

It is very important to use combat simulation in personnel training and preparing them for different war scenarios. Simulation modeling and analysis methodologies gives an opportunity to staff officers and commanders to measure the effectiveness of their plans and take necessary precautions. In a simulated environment, different combat scenarios can be tried without actually deploying the units to the combat area and getting ‘losts, costs, and risks’. As one of the most complicated and decisive operations on the road to victory, ‘air assault operations’ are high-risk, high-payoff operations that, when properly planned and vigorously executed, allow commanders to take the initiative in combat areas. In this study, we develop a simulation system called the Air Assault Operations Simulation Model (AAOSM) that allows planners to: (1) analyze air assault operations early in the decision process and refine those models as their decision process evolves, (2) perform ‘ bottleneck analysis’ ...

Computers & Mathematics with Applications, 1987

A general framework for the utilization of large numbers of optimal pursuit-evasion algorithms, as applied to air combat, is described. The framework is based upon and is driven by artificial intelligence concepts. The method employed involves the valuation of alternative tactical stratcgies and maneuvers through a goal system and pilot-derived expert data bases. The system is designed to display the most promising strategies to the pilot for a final decision. Two aspects of the concept above are described here: the general framework and a specific implementation for a synthetic method of flight and fire control system optimization. Details of the implementation, based on off-the-shelf hardware and a standard programming lanuage, are also given. Potential utilization of these concepts includes other areas as well: submarine warfare and satellite based weapon systems are two possible additional applications. Nonmilitary applications are air trafl~c control and optimal scheduling.

This advanced tutorial introduces the engineering principles of combat modeling and distributed simulation. It starts with the historical context and introduces terms and definitions as well as guidelines of interest in this domain. The combat modeling section introduces the main concepts for modeling of the environment, movement, effects, sensing, communications, and decision making. The distributed simulation section focuses on the challenges of current simulation interoperability standards that support dealing with them. Overall, the tutorial shall introduce the scholar to the operational view (what needs to be modeled), the conceptual view (how to do combat modeling), and the technical view (how to conduct distributed simulation).

1997

Background Since 1983 the Defense Advanced Research Projects Agency (DARPA) has exerted a significant effort to develop a realistic, distributed, synthetic battlefield that could be used for training, mission planning and rehearsal, tactics and doctrine development, and weapon-system concept evaluation. The underlying distributed interactive simulation (DIS) technology builds large-scale simulations from a set of independent simulators linked together in a network (DIS Steering Committee 1994).

2009

Abstract: High-fidelity modelling for motion, response to physical stimuli and attack behaviours along with realistic control are vital requirements for training-critical military simulations. In addition, whenever simulation components are built on different infrastructures, maintaining coordination becomes a challenging problem. There are several COTS frameworks that facilitate development of computer generated forces (CGF), scenario management and run control for distributed simulations.

Development and optimization of simulation models and methods for controlling virtual artillery units in game scenarios, 2023

In the realm of modern video game development, special attention is given to the simulation of artillery systems, which play a crucial role in various military-themed games. This research presents a mathematical model for simulating the actions of a virtual artillery system. The model is designed to manage the execution of combat tasks, including targeting destruction with a specified number of shells and incorporating the strategic movement between firing positions to minimize detection and attack by enemy forces in the game. The model presumes that all shots are effective and equates the number of firing positions to the number of shots, with a minimum of one shot per position. The model's dynamics do not allow for returning to previous positions, adding a layer of complexity and realism to the gameplay. Movement simulations between positions are designed along virtual roads of varying quality, enhancing the strategic elements of the game. A method for determining the optimal strategy for the artillery system's actions has been developed, introducing the concept of the current structure of combat task execution. This problem-solving approach falls within the realm of Pareto-oriented tasks or dynamic programming challenges. The computational method of the model is based on a general algorithm, underpinned by specialized additional algorithms. Results from this model demonstrate the feasibility of completing combat tasks effectively, with a maximum of two shots per firing position. The research differentiates between defensive and offensive tactics in gameplay, suggesting that while a strategy involving ten shots per target aligns with defensive gameplay, a strategy with four shots per target aligns with offensive actions. Consequently, the "shot-and-scoot" tactic in an offensive context can be aptly termed as "hid-and-shot".

1994

knowledge about two classes of one-versus-This article reports on recent progress one (1-v-1) Beyond Visual Range (BVR) in the development of TacAir-Soar, an tactical air scenarios. In the non-jinking intelligent automated agent for tactical air bogey scenarios, one plane (the non-jinking simulation. This includes progress in bogey) is unarmed and maintains a straightexpanding the agent's coverage of the and-level flight path. The other plane is tactical air domain, progress in enhancing armed with long-range radar-guided, the quality of the agent's behavior, and medium-range radar-guided, and short-range progress in building an infrastructure for infrared-guided missiles. Its task is to set up research and development in this area. for a sequence of missile shots, at increasingly shorter ranges, until the non