Abstract
With increasing defence budget constraints and environmental safety concerns on employing live exercises for training, there has been a reinforced focus end considerable efforts on designing military training simulators using modelling, simulation, and analysis for operational analyses and training. Air Warfare Simulation System is an agent-oriented virtual warfare simulator that is designed using these concepts for operational analysis and course of action analysis for training. A critical factor that decides the next course of action and hence the results of the simulation is the skill, experience, situation awareness of the pilot in the aircraft cockpit and the pilots’ decision making ability in the cockpit. Advances in combat aircraft avionics and onboard automation, information from onboard and ground sensors and satellites poses a threat in terms of information and cognitive overload to the pilot, and triggering conditions that makes decision making a difficult task. Several mathematical models of the pilot behaviour, typically based on control theory, have been proposed in literature. In this work, we describe a novel approach based on soft computing and Computational Intelligence paradigms called ANFIS, a neuro-fuzzy hybridization technique, to model the pilot agent and its behaviour characteristics in the warfare simulator. This emerges as an interesting problem as the decisions made are dynamic and depend upon the actions taken by enemy. We also build a pilots’ database that represents the specific cognitive characteristics, skills, training experience, and as factors that affect the pilot’s decision making and study its effect on the results obtained from the warfare simulation. We illustrate the methodology with suitable examples and lessons drawn from the virtual air warfare simulator.
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Vijay Rao, D., Balas-Timar, D. (2014). A Soft Computing Approach to Model Human Factors in Air Warfare Simulation System. In: Balas, V., Koprinkova-Hristova, P., Jain, L. (eds) Innovations in Intelligent Machines-5. Studies in Computational Intelligence, vol 561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43370-6_5
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