We present a general framework for studying heuristics for planning in the belief space. Earlier work has focused on giving implementations of heuristics that work well on benchma...
Scaling conformant planning is a problem that has received much attention of late. Many planners solve the problem as a search in the space of belief states, and some heuristic gu...
State estimation in multiagent settings involves updating an agent’s belief over the physical states and the space of other agents’ models. Performance of the previous approac...
We present a new method for carrying out state estimation in multiagent settings that are characterized by continuous or large discrete state spaces. State estimation in multiagen...
Partially observable Markov decision processes (POMDPs) have been
successfully applied to various robot motion planning tasks under uncertainty.
However, most existing POMDP algo...
Haoyu Bai, David Hsu, Wee Sun Lee, and Vien A. Ngo