Multi-agent planning for mixed human-robot environments faces significant challenges. Current methodologies, often relying on data-driven human motion prediction and hand-tuned costs, struggle with long-term reasoning and complex interactions. Researchers aim to solve two primary issues: developing human-compatible strategies without clear equilibrium concepts and generating sufficient samples for learning algorithms. Existing approaches, while effective in scaling […]
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