4 papers
Coordination Matters: Evaluation of Cooperative Multi-Agent Reinforcement Learning
Maria Ana Cardei, Matthew Landers, Afsaneh Doryab
Cooperative multi-agent reinforcement learning (MARL) benchmarks commonly emphasize aggregate outcomes such as return, success rate, or completion time. While essential, these metr…
SAINT: Attention-Based Policies for Discrete Combinatorial Action Spaces
Matthew Landers, Taylor W. Killian, Thomas Hartvigsen +1
The combinatorial structure of many real-world action spaces leads to exponential growth in the number of possible actions, limiting the effectiveness of conventional reinforcement…
Improving and Accelerating Offline RL in Large Discrete Action Spaces with Structured Policy Initialization
Matthew Landers, Taylor W. Killian, Thomas Hartvigsen +1
Reinforcement learning in discrete combinatorial action spaces requires searching over exponentially many joint actions to simultaneously select multiple sub-actions that form cohe…
BraVE: Offline Reinforcement Learning for Discrete Combinatorial Action Spaces
Matthew Landers, Taylor W. Killian, Hugo Barnes +2
Offline reinforcement learning in high-dimensional, discrete action spaces is challenging due to the exponential scaling of the joint action space with the number of sub-actions an…