Hierarchical Multi-Agent Reinforcement Learning for Air Combat Maneuvering

1 code implementation • 20 Sep 2023 • Ardian Selmonaj, Oleg Szehr, Giacomo Del Rio, Alessandro Antonucci, Adrian Schneider, Michael Rüegsegger

In our framework, the decision-making process is divided into two stages of abstraction, where heterogeneous low-level policies control the action of individual units, and a high-level commander policy issues macro commands given the overall mission targets.

Decision Making Multi-agent Reinforcement Learning +1