A decentralized reinforcement-learning framework using virtual pheromone marks and local map sharing outperforms MARL baselines for finding dynamic targets in simulated unknown grid environments.
A multi-agent reinforcement learning method for swarm robots in space collaborative exploration
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PILOC: A Pheromone Inverse Guidance Mechanism and Local-Communication Framework for Dynamic Target Search of Multi-Agent in Unknown Environments
A decentralized reinforcement-learning framework using virtual pheromone marks and local map sharing outperforms MARL baselines for finding dynamic targets in simulated unknown grid environments.