63 citations · 212 across the 18 of their papers we have counts for
4 papers · 1 filter
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees
Zichuan Liu, Yuanyang Zhu, Zhi Wang +2
While achieving tremendous success in various fields, existing multi-agent reinforcement learning (MARL) with a black-box neural network makes decisions in an opaque manner that hi…
A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning
Zhi Wang, Chunlin Chen, Daoyi Dong
While reinforcement learning (RL) algorithms are achieving state-of-the-art performance in various challenging tasks, they can easily encounter catastrophic forgetting or interfere…
Efficient Bayesian Policy Reuse with a Scalable Observation Model in Deep Reinforcement Learning
Jinmei Liu, Zhi Wang, Chunlin Chen +1
Bayesian policy reuse (BPR) is a general policy transfer framework for selecting a source policy from an offline library by inferring the task belief based on some observation sign…
Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation
Donghan Xie, Zhi Wang, Chunlin Chen +1
Multi-agent settings remain a fundamental challenge in the reinforcement learning (RL) domain due to the partial observability and the lack of accurate real-time interactions acros…