19 citations · 60 across the 23 of their papers we have counts for
4 papers · 1 filter
Scalability Bottlenecks in Multi-Agent Reinforcement Learning Systems
Kailash Gogineni, Peng Wei, Tian Lan +1
Multi-Agent Reinforcement Learning (MARL) is a promising area of research that can model and control multiple, autonomous decision-making agents. During online training, MARL algor…
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Multi-agent reinforcement learning (MARL) has witnessed significant progress with the development of value function factorization methods. It allows optimizing a joint action-value…
Learning Multi-agent Skills for Tabular Reinforcement Learning using Factor Graphs
Jiayu Chen, Jingdi Chen, Tian Lan +1
Covering skill (a.k.a., option) discovery has been developed to improve the exploration of reinforcement learning in single-agent scenarios with sparse reward signals, through conn…
Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Value function factorization via centralized training and decentralized execution is promising for solving cooperative multi-agent reinforcement tasks. One of the approaches in thi…