Abstract
AbstractThe high operational cost of aircraft, limited availability of air space, and strict safety regulations make training of fighter pilots increasingly challenging. By integrating Live, Virtual, and Constructive simulation resources, efficiency and effectiveness can be improved. In particular, if constructive simulations, which provide synthetic agents operating synthetic vehicles, were used to a higher degree, complex training scenarios could be realised at low cost, the need for support personnel could be reduced, and training availability could be improved. In this work, inspired by the recent improvements of techniques for artificial intelligence, we take a user perspective and investigate how intelligent, learning agents could help build future training systems. Through a domain analysis, a user study, and practical experiments, we identify important agent capabilities and characteristics, and then discuss design approaches and solution concepts for training systems to utilise learning agents for improved training value.
Highlights
Providing efficient and effective training solutions for fighter pilots is becoming increasingly challenging
From a qualitative point of view, when observing the outcome of each iteration, it could be seen that both teams were trying to split up and have one pilot approach each threat, which is the optimal tactic for the scenario
The major complaint was that when there was a conflict in target allocation, with a human pilot and an agent approaching the same target, agents might not immediately realise this and select a new target
Summary
Providing efficient and effective training solutions for fighter pilots is becoming increasingly challenging. The purpose of the analysis is to identify constraints imposed on training providers when using different types of simulation resources, and to model the patterns of decision-making a synthetic agent must be capable of if it is to replace human role-players in air combat scenarios. The aim is to illustrate to what extent perception, decisions, and actions are supported by the automation of the aircraft or pre-planned procedures, and which parts of aircraft control that must be handled by the pilot alone This information gives insight regarding requirements that must be fulfilled by synthetic agents that are to replace human pilots in training scenarios, and how to design the interface between the agent and the aircraft model, including its tactical systems. Instructors could use their domain knowledge to specify the goals and characteristics of the agents
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