151 citations · 276 across the 14 of their papers we have counts for
3 papers · 1 filter
Influence-Based Multi-Agent Exploration
Tonghan Wang, Jianhao Wang, Yi Wu +1
Intrinsically motivated reinforcement learning aims to address the exploration challenge for sparse-reward tasks. However, the study of exploration methods in transition-dependent…
Learning Nearly Decomposable Value Functions Via Communication Minimization
Tonghan Wang, Jianhao Wang, Chongyi Zheng +1
Reinforcement learning encounters major challenges in multi-agent settings, such as scalability and non-stationarity. Recently, value function factorization learning emerges as a p…
Object-Oriented Dynamics Learning through Multi-Level Abstraction
Guangxiang Zhu, Jianhao Wang, Zhizhou Ren +2
Object-based approaches for learning action-conditioned dynamics has demonstrated promise for generalization and interpretability. However, existing approaches suffer from structur…