Competitive Multi-agent Deep Reinforcement Learning with Counterfactual Thinking

@article{Wang2019CompetitiveMD,
  title={Competitive Multi-agent Deep Reinforcement Learning with Counterfactual Thinking},
  author={Yue Wang and Yao Wan and Chenwei Zhang and Lixin Cui and Lu Bai and Philip S. Yu},
  journal={2019 IEEE International Conference on Data Mining (ICDM)},
  year={2019},
  pages={1366-1371}
}
  • Yue Wang, Yao Wan, +3 authors Philip S. Yu
  • Published in
    IEEE International Conference…
    2019
  • Computer Science, Mathematics
  • Counterfactual thinking describes a psychological phenomenon that people re-infer the possible results with different solutions about things that have already happened. It helps people to gain more experience from mistakes and thus to perform better in similar future tasks. This paper investigates the counterfactual thinking for agents to find optimal decision-making strategies in multi-agent reinforcement learning environments. In particular, we propose a multi-agent deep reinforcement… CONTINUE READING

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