Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
The research community has witnessed a large interest in monitoring large scale distributed systems. In these applications typically we wish to monitor a global system condition wh...
Ali Abbasi, Ahmad Khonsari, Mohammad Sadegh Talebi
Abstract. This work addresses a class of total-variation based multilabeling problems over a spatially continuous image domain, where the data fidelity term can be any bounded fun...
In robotic navigation, path planning is aimed at getting the optimum collision-free
path between a starting and target locations. The optimality criterion depends on
the surround...
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...