2 citations · 6 across the 7 of their papers we have counts for
3 papers · 1 filter
Regularize! Don't Mix: Multi-Agent Reinforcement Learning without Explicit Centralized Structures
Chapman Siu, Jason Traish, Richard Yi Da Xu
We propose using regularization for Multi-Agent Reinforcement Learning rather than learning explicit cooperative structures called {\em Multi-Agent Regularized Q-learning} (MARQ).…
Dual Behavior Regularized Reinforcement Learning
Chapman Siu, Jason Traish, Richard Yi Da Xu
Reinforcement learning has been shown to perform a range of complex tasks through interaction with an environment or collected leveraging experience. However, many of these approac…
Greedy UnMixing for Q-Learning in Multi-Agent Reinforcement Learning
Chapman Siu, Jason Traish, Richard Yi Da Xu
This paper introduces Greedy UnMix (GUM) for cooperative multi-agent reinforcement learning (MARL). Greedy UnMix aims to avoid scenarios where MARL methods fail due to overestimati…