38 citations · 94 across the 7 of their papers we have counts for
4 papers · 1 filter
Flow-based Recurrent Belief State Learning for POMDPs
Xiaoyu Chen, Yao Mu, Ping Luo +2
Partially Observable Markov Decision Process (POMDP) provides a principled and generic framework to model real world sequential decision making processes but yet remains unsolved,…
Learning Emergent Discrete Message Communication for Cooperative Reinforcement Learning
Sheng Li, Yutai Zhou, Ross Allen +1
Communication is a important factor that enables agents work cooperatively in multi-agent reinforcement learning (MARL). Most previous work uses continuous message communication wh…
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning
Sheng Li, Jayesh K. Gupta, Peter Morales +2
Multi-agent reinforcement learning (MARL) requires coordination to efficiently solve certain tasks. Fully centralized control is often infeasible in such domains due to the size of…
Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning
Sheng Li, Maxim Egorov, Mykel Kochenderfer
New methodologies will be needed to ensure the airspace remains safe and efficient as traffic densities rise to accommodate new unmanned operations. This paper explores how unmanne…