Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Decentralized partially observable Markov decision processes (DEC-POMDPs) form a general framework for planning for groups of cooperating agents that inhabit a stochastic and part...
Matthijs T. J. Spaan, Geoffrey J. Gordon, Nikos A....
Large systems of agents deployed in a real-world environment face threats to their problem solving performance that are independent of the complexity of the problem or the charact...
— We introduce a novel strategy for data processing in Wireless Sensor Networks (WSNs) in the case of emergency fire evacuation with stringent delay constraints. Such networks sh...