—We consider opportunistic communications over multiple channels where the state (“good” or “bad”) of each channel evolves as independent and identically distributed Mark...
Markov decision processes (MDPs) and contingency planning (CP) are two widely used approaches to planning under uncertainty. MDPs are attractive because the model is extremely gen...
Many applications of networks of agents, including mobile sensor networks, unmanned air vehicles, autonomous underwater vehicles, involve 100s of agents acting collaboratively und...
Janusz Marecki, Tapana Gupta, Pradeep Varakantham,...
We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual...
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
Michael L. Littman, Anthony R. Cassandra, Leslie P...