5 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 5 cited
Non-local Policy Optimization via Diversity-regularized Collaborative Exploration
Zhenghao Peng, Hao Sun, Bolei Zhou
Conventional Reinforcement Learning (RL) algorithms usually have one single agent learning to solve the task independently. As a result, the agent can only explore a limited part o…
cs.LG2020
Evolutionary Stochastic Policy Distillation
Hao Sun, Xinyu Pan, Bo Dai +2
Solving the Goal-Conditioned Reward Sparse (GCRS) task is a challenging reinforcement learning problem due to the sparsity of reward signals. In this work, we propose a new formula…
cs.LG2019
Risk-Averse Trust Region Optimization for Reward-Volatility Reduction
Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori +2
In real-world decision-making problems, for instance in the fields of finance, robotics or autonomous driving, keeping uncertainty under control is as important as maximizing expec…