A survey of air combat behavior modeling using machine learning

arXiv:2404.13954v1 Announce Type: new
Abstract: With the recent advances in machine learning, creating agents that behave realistically in simulated air combat has become a growing field of interest. This survey explores the application of machine learning techniques for modeling air combat behavior, motivated by the potential to enhance simulation-based pilot training. Current simulated entities tend to lack realistic behavior, and traditional behavior modeling is labor-intensive and prone to loss of essential domain knowledge between development steps. Advancements in reinforcement learning …

abstract advances agents application arxiv become behavior combat cs.ai cs.lg cs.ma machine machine learning machine learning techniques modeling pilot simulation survey type