Heterogeneous Hierarchical Multi Agent Reinforcement Learning for Air Combat
A Gym Dogfighting Simulation Benchmark for Reinforcement Learning Research
CHECKMATE is a fast executing, agent-based simulation of air combat intended to support development of advanced algorithms
🚀 Master War Thunder with advanced tactics, weak spots, and combat strategies. Complete guide for Ground, Air, and Naval battles with SEO optimization.
A high-fidelity beyond-visual-range (BVR) swarm drone air combat simulation platform on JSBSim. Evaluates strategy robustness under non-ideal sensing to bridge sim-to-real gap. Integrates AIM-120C-5 missile dynamics, absolute-state Kalman filter, and Tacview visualization. Designed for academic research on multi-agent coordination and RL validation
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