— We consider decision making in a Markovian setup where the reward parameters are not known in advance. Our performance criterion is the gap between the performance of the best ...
We introduce the generalized semi-Markov decision process (GSMDP) as an extension of continuous-time MDPs and semi-Markov decision processes (SMDPs) for modeling stochastic decisi...
Decentralized Markov Decision Processes (DEC-MDPs) are a popular model of agent-coordination problems in domains with uncertainty and time constraints but very difficult to solve...
We consider a scenario where devices with multiple networking capabilities access networks with heterogeneous characteristics. In such a setting, we address the problem of effici...
Jatinder Pal Singh, Tansu Alpcan, Piyush Agrawal, ...
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...