5 citations · 7 across the 3 of their papers we have counts for
5 papers
Niching Diversity Estimation for Multi-modal Multi-objective Optimization
Yiming Peng, Hisao Ishibuchi
Niching is an important and widely used technique in evolutionary multi-objective optimization. Its applications mainly focus on maintaining diversity and avoiding early convergenc…
A Decomposition-based Large-scale Multi-modal Multi-objective Optimization Algorithm
Yiming Peng, Hisao Ishibuchi
A multi-modal multi-objective optimization problem is a special kind of multi-objective optimization problem with multiple Pareto subsets. In this paper, we propose an efficient mu…
Off-Policy Actor-Critic in an Ensemble: Achieving Maximum General Entropy and Effective Environment Exploration in Deep Reinforcement Learning
Gang Chen, Yiming Peng
We propose a new policy iteration theory as an important extension of soft policy iteration and Soft Actor-Critic (SAC), one of the most efficient model free algorithms for deep re…
Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization
Gang Chen, Yiming Peng, Mengjie Zhang
Recently deep reinforcement learning (DRL) has achieved outstanding success on solving many difficult and large-scale RL problems. However the high sample cost required for effecti…
An Adaptive Clipping Approach for Proximal Policy Optimization
Gang Chen, Yiming Peng, Mengjie Zhang
Very recently proximal policy optimization (PPO) algorithms have been proposed as first-order optimization methods for effective reinforcement learning. While PPO is inspired by th…