2 papers
cs.RO2026
Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learning
Kanghoon Lee, Matthew M. Sato, Jinnyeong Yang +7
Monitoring human activity in indoor environments is important for applications such as facility management, safety assessment, and space utilization analysis. While mobile robot te…
cs.MA2024
Distributed Online Planning for Min-Max Problems in Networked Markov Games
Alexandros E. Tzikas, Jinkyoo Park, Mykel J. Kochenderfer +1
Min-max problems are important in multi-agent sequential decision-making because they improve the performance of the worst-performing agent in the network. However, solving the mul…