most citedCommon Information based Approximate State Representations in Multi-Agent Reinforcement Learning

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021

Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure

Hsu Kao, Chen-Yu Wei, Vijay Subramanian

Multi-agent reinforcement learning (MARL) problems are challenging due to information asymmetry. To overcome this challenge, existing methods often require high level of coordinati…

cs.LG2021★ 2 cited

Common Information based Approximate State Representations in Multi-Agent Reinforcement Learning

Hsu Kao, Vijay Subramanian

Due to information asymmetry, finding optimal policies for Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) is hard with the complexity growing doubly expo…