most citedBackpropagation through Time and Space: Learning Numerical Methods with Multi-Agent Reinforcement Learning

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cs.LG2022★ 1 cited

Backpropagation through Time and Space: Learning Numerical Methods with Multi-Agent Reinforcement Learning

Elliot Way, Dheeraj S. K. Kapilavai, Yiwei Fu +1

We introduce Backpropagation Through Time and Space (BPTTS), a method for training a recurrent spatio-temporal neural network, that is used in a homogeneous multi-agent reinforceme…

cs.LG2019

Diverse Exploration via Conjugate Policies for Policy Gradient Methods

Andrew Cohen, Xingye Qiao, Lei Yu +2

We address the challenge of effective exploration while maintaining good performance in policy gradient methods. As a solution, we propose diverse exploration (DE) via conjugate po…