3 papers
cs.AI2025
Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics
Yang You, Alex Schutz, Zhikun Li +3
Many high-level multi-agent planning problems, including multi-robot navigation and path planning, can be effectively modeled using deterministic actions and observations. In this…
cs.AI2025
Partially Observable Monte-Carlo Graph Search
Yang You, Vincent Thomas, Alex Schutz +3
Currently, large partially observable Markov decision processes (POMDPs) are often solved by sampling-based online methods which interleave planning and execution phases. However,…
cs.RO2025
A Finite-State Controller Based Offline Solver for Deterministic POMDPs
Alex Schutz, Yang You, Matias Mattamala +3
Deterministic partially observable Markov decision processes (DetPOMDPs) often arise in planning problems where the agent is uncertain about its environmental state but can act and…