most citedHierarchical Multi-Agent Reinforcement Learning for Air Combat Maneuvering

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cs.AI2025

Enhancing Aerial Combat Tactics through Hierarchical Multi-Agent Reinforcement Learning

Ardian Selmonaj, Oleg Szehr, Giacomo Del Rio +3

This work presents a Hierarchical Multi-Agent Reinforcement Learning framework for analyzing simulated air combat scenarios involving heterogeneous agents. The objective is to iden…