PNS: Population-Guided Novelty Search for Reinforcement Learning in Hard Exploration Environments
Qihao Liu,Yujia Wang,Xiaofeng Liu,Qihao Liu,Yujia Wang,Xiaofeng Liu
Reinforcement Learning (RL) has made remarkable achievements, but it still suffers from inadequate exploration strategies, sparse reward signals, and deceptive reward functions. To alleviate these problems, a Population-guided Novelty Search (PNS) parallel learning method is proposed in this paper. In PNS, the population is divided into multiple sub-populations, each of which has one chief agent a...
