most citedDiversity-Driven Exploration Strategy for Deep Reinforcement Learning

69 citations · 121 across the 4 of their papers we have counts for

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cs.AI2018★ 69 cited

Diversity-Driven Exploration Strategy for Deep Reinforcement Learning

Zhang-Wei Hong, Tzu-Yun Shann, Shih-Yang Su +2

Efficient exploration remains a challenging research problem in reinforcement learning, especially when an environment contains large state spaces, deceptive local optima, or spars…

cs.AI2017★ 43 cited

A Deep Policy Inference Q-Network for Multi-Agent Systems

Zhang-Wei Hong, Shih-Yang Su, Tzu-Yun Shann +2

We present DPIQN, a deep policy inference Q-network that targets multi-agent systems composed of controllable agents, collaborators, and opponents that interact with each other. We…