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Aditya Kapoor

2 accepted papers

2024

Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environments

NeurIPS 2024poster

The ability of Language Models (LMs) to understand natural language makes them a powerful tool for parsing human instructions into task plans for autonomous robots. Unlike traditional planning methods that rely on domain-specific knowledge and handcrafted rules, LMs generalize from diverse data and…

2022

Learning Cooperative Multi-Agent Policies With Partial Reward Decoupling

RA-L 2022

One of the preeminent obstacles to scaling multi-agent reinforcement learning to large numbers of agents is assigning credit to individual agents’ actions. In this letter, we address this credit assignment problem with an approach that we call <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" x

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