Optimal plans in Constrained Partially Observable Markov Decision Processes (CPOMDPs)
maximize reward objectives while satisfying hard cost constraints, generalizing safe …

Decentralized partially observable Markov decision processes with communication (Dec-
POMDP-Com) provide a framework for multiagent decision making under uncertainty, but …

To plan safely in uncertain environments, agents must balance utility with safety constraints.
Safe planning problems can be modeled as a chance-constrained partially observable …

Autonomous robot teams have the potential to revolutionize the way we approach many
problems, ranging from transportation to active sensing for weather science. However, to …

Beam-agile radars have the potential to learn scheduling policies requiring only a holistic
belief constructed from past observations. Rewarding improvements to belief directly …

From warehouses and manufacturing lines to homes and offices, from roads and seas, to
skies and space, autonomous systems promise to improve efficiency, unlock human …

A growing population will require more metal in order to sustainably build a high quality of
life. However, there have been fewer discoveries of mineral deposits due to constrained …

Abstract Radar Resource Management (RRM) aims to optimize the allocation of resources
in a multifunction radar system. We focus on searching for unknown targets and tracking …

To plan safely in uncertain environments, agents must balance utility with safety constraints.
Safe planning problems can be modeled as a chanceconstrained partially observable …