Papers › Represented Value Function Approach for Large Scale Multi Agent Reinforcement Learning

Represented Value Function Approach for Large Scale Multi Agent Reinforcement Learning

4 Jan 2020arXiv:2001.01096archive 2025-07-28

Wei-Ya Ren

In this paper, we consider the problem of large scale multi agent reinforcement learning. Firstly, we studied the representation problem of the pairwise value function to reduce the complexity of the interactions among agents. Secondly, we adopt a l2-norm trick to ensure the trivial term of the approximated value function is bounded. Thirdly, experimental results on battle game demonstrate the effectiveness of the proposed approach.

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Multi-agent Reinforcement Learning Reinforcement Learning Reinforcement Learning (RL)reinforcement-learning

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