52 citations · 172 across the 27 of their papers we have counts for
5 papers · 1 filter
Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings
Kingsley Nweye, Bo Liu, Peter Stone +1
Building upon prior research that highlighted the need for standardizing environments for building control research, and inspired by recently introduced challenges for real life re…
Conflict-Averse Gradient Descent for Multi-task Learning
Bo Liu, Xingchao Liu, Xiaojie Jin +2
The goal of multi-task learning is to enable more efficient learning than single task learning by sharing model structures for a diverse set of tasks. A standard multi-task learnin…
Team Orienteering Coverage Planning with Uncertain Reward
Bo Liu, Xuesu Xiao, Peter Stone
Many municipalities and large organizations have fleets of vehicles that need to be coordinated for tasks such as garbage collection or infrastructure inspection. Motivated by this…
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition
Bo Liu, Qiang Liu, Peter Stone +3
In real-world multi-agent systems, agents with different capabilities may join or leave without altering the team's overarching goals. Coordinating teams with such dynamic composit…
APPL: Adaptive Planner Parameter Learning
Xuesu Xiao, Zizhao Wang, Zifan Xu +5
While current autonomous navigation systems allow robots to successfully drive themselves from one point to another in specific environments, they typically require extensive manua…