A Neuro-Fuzzy Hybridization Approach to Model the Pilot Agent in Air Warfare Simulation Systems

17-1-5.jpg
17-1-5.jpg

A Neuro-Fuzzy Hybridization Approach to Model the Pilot Agent in Air Warfare Simulation Systems

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Author(s): Dana Balas-Timar; D. Vijay Rao
No pages: 8
Year: 2014
Article ID: 17-1-5
Keywords: agent-based simulation, cognitive overload, decision making, military warfare analysis, neuro-fuzzy hybridization, situational awareness, training and analysis
Format: Electronic (PDF)

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Abstract: Intelligent military training simulators offer an economic, ecologically acceptable, training platform that approximates real-life situations, and facilitate perception and interaction in a relatively unconstrained situated-learning paradigm that supports a comprehensive learning strategy. Human factors such as skills, experience, situation awareness and pilot decision-making ability in the cockpit are critical factors that determine the decision processes, course of action, and results of the simulation. Air Warfare Simulation System, a virtual warfare analysis software has been developed for planning, analysis, and evaluation of mission effectiveness in air-tasking operations where human factors play a major role in training and learning. In this paper, we propose a Neuro-fuzzy hybridization technique, Adaptive Neuro-Fuzzy Inference System (ANFIS) to model the human factors of the pilot agent and behaviour characteristics in the warfare simulator. A pilot database has been developed in order to store the specific cognitive characteristics, skills, and training experience, which affect pilot decision making. Finally, their effect on the mission effectiveness obtained by the warfare simulation has been studied. The methodology of modelling human factors of pilots using ANFIS is illustrated with suitable examples, and lessons drawn from the virtual air warfare simulator are discussed.