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Found 2 papers, 1 papers with code
Strategic Maneuver and Disruption with Reinforcement Learning Approaches for Multi-Agent Coordination
Reinforcement learning (RL) approaches can illuminate emergent behaviors that facilitate coordination across teams of agents as part of a multi-agent system (MAS), which can provide windows of opportunity in various military tasks.
Scalable Reinforcement Learning Policies for Multi-Agent Control
Our method can handle an arbitrary number of pursuers and targets; we show results for tasks consisting up to 1000 pursuers tracking 1000 targets.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
