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Relevant bibliographies by topics / Computer Generated Forces (CGF)

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Journal articles

Academic literature on the topic 'Computer Generated Forces (CGF)'

Author: Grafiati

Published: 26 October 2023

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Journal articles on the topic "Computer Generated Forces (CGF)"

1

Archer, Rick, Brett Walters, and Amy Yow. "Modeling Training Effects in Computer Generated Forces." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 11 (2000): 402–5. http://dx.doi.org/10.1177/154193120004401119.

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The use of Computer Generated Forces (CGF) in simulations ranges from small human performance models to large scale Advanced Distributed Simulations (ADS). CGF have been used to assess human performance aspects of system designs and to augment man-in-the-loop simulators with friendly and opposing forces to make simulated battlefield training exercises realistic. However, the current human performance models and ADS available to system designers, trainers, and resource allocation analysts do not include the effects of training on the performance of the CGF. For the most part, the CGF entities i

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2

Chen, Jian, Yan Li Yang, and Zhi Guo Liu. "Research on Method of Property Verification of Multi-Agent System CGF Architecture Model." Applied Mechanics and Materials 344 (July 2013): 294–99. http://dx.doi.org/10.4028/www.scientific.net/amm.344.294.

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When Multi-agent system theory is used to the research of CGF(Computer Generated Forces), making up a correct and believable model is critical. In this article, we deal with the foundation,exit and update of Agent as well as the reconfiguration of system framework of CGF aiming at the problem of model evolvement caused by many Agent in CGF system always changing and show the validity of the model using INA.

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3

Hutton, Robert J. B., Walter Warwick, Terry Stanard, Patricia L. McDermott, and Stacey McIlwaine. "Computational Model of Recognition-Primed Decisions (RPD): Improving Realism in Computer-Generated Forces (CGF)." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 45, no. 26 (2001): 1833–37. http://dx.doi.org/10.1177/154193120104502607.

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4

Park, Daekuk, and Namsuk Cho. "A Study on Reinforcement Learning Method for the Deception Behavior : Focusing on Marine Corps Amphibious Demonstrations." Journal of the Korea Institute of Military Science and Technology 25, no. 4 (2022): 390–400. http://dx.doi.org/10.9766/kimst.2022.25.4.390.

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Military deception is an action executed to deliberately mislead enemy’s decision by deceiving friendly forces intention. In the lessons learned from war history, deception appears to be a critical factor in the battlefield for successful operations. As training using war-game simulation is growing more important, it is become necessary to implement military deception in war-game model. However, there is no logics or rules proven to be effective for CGF(Computer Generated Forces) to conduct deception behavior automatically. In this study, we investigate methodologies for CGF to learn and condu

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5

Verdesca, Marlo, Jaeson Munro, Michael Hoffman, Maria Bauer, and Dinesh Manocha. "Using Graphics Processor Units to Accelerate OneSAF: A Case Study in Technology Transition." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 3, no. 3 (2006): 177–87. http://dx.doi.org/10.1177/154851290600300305.

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Ongoing research aims to accelerate the runtime processing speed of the One Semi-Automated Forces (OneSAF) Computer Generated Forces (CGF) simulation by converting and migrating some of the core algorithms from the host central processing unit (CPU) to an onboard auxiliary graphics processor unit (GPU). In this research the GPU chip is regarded as a surrogate stream processor, and appropriate algorithms are designed to map to the GPU architecture. Processing speed gains are realized both through computational capabilities of the GPU as well as through offloading of the host CPU. Technology tra

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6

Yao, Jian, Qiwang Huang, and Weiping Wang. "Adaptive CGFs Based on Grammatical Evolution." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/197306.

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Computer generated forces (CGFs) play blue or red units in military simulations for personnel training and weapon systems evaluation. Traditionally, CGFs are controlled through rule-based scripts, despite the doctrine-driven behavior of CGFs being rigid and predictable. Furthermore, CGFs are often tricked by trainees or fail to adapt to new situations (e.g., changes in battle field or update in weapon systems), and, in most cases, the subject matter experts (SMEs) review and redesign a large amount of CGF scripts for new scenarios or training tasks, which is both challenging and time-consuming

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7

Massei, Marina, Alberto Tremori, Vera Novak, et al. "Obesity Epidemic Simulation Based on Behavioral Models and Intelligent Agents." International Journal of Privacy and Health Information Management 1, no. 2 (2013): 96–114. http://dx.doi.org/10.4018/ijphim.2013070107.

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This research work is aimed at proposing a simulation model based on Intelligent Agents devoted to reproduce human behavior influence over the evolution and impact of obesity epidemics. Indeed, obesity is a real big problem for both USA and European countries, so it is necessary to take under control this phenomenon and, above all, to support Agencies and Nations with simulation models in order to promote specific actions, to guarantee population healthy and to reduce the related social costs. To this end, taking advantage of previous experiences on Human Behavior Models, a Library including I

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8

Deng, Jian Jun, Da Wu, and Li Liu. "Research on Modeling in CGF System of Air Defense Missile." Applied Mechanics and Materials 734 (February 2015): 350–53. http://dx.doi.org/10.4028/www.scientific.net/amm.734.350.

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The Computer Generated Force (CGF) system was introduced and the model structure of CGF system was discussed. The entities' model of missile was designed, it includes operator model and mobile controller and dynamic model of missile, different missile can be simulated by given different parameters of performance with the model. The behavior modeling based on Finite State Machine of CGF was studied, it could generate targeted behavior to the changing situation of combat environment. The simulation results show that the modeling method is reasonable and valid.

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9

Han, Chang Hee. "Group Behavior Simulation for Computer-generated Forces." Joural of the Korea Entertainment Industry Association 10, no. 1 (2016): 323. http://dx.doi.org/10.21184/jkeia.2016.02.10.1.323.

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10

Li, Ni, Min He, Zhi Ming Ren, and Guang Hong Gong. "CGF-SDP: Development of Simulation Scenario and Scenario Editor." Applied Mechanics and Materials 441 (December 2013): 431–34. http://dx.doi.org/10.4028/www.scientific.net/amm.441.431.

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Military Scenario Definition Language (MSDL) is intended to provide a standard mechanism for loading Military Scenarios independent of the applications. Some customized scenario specifications lack scalability and interoperability with Command and Control (C2) applications. And how to integrate MSDL with simulation models still needs further implementation. This paper extended and modified MSDL to propose a feasible simulation scenario specification based on our existed CGF (Computer Generated Force) model system. A CGF-SDP (Scenario Development tool) was also developed to facilitate generatin

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