This paper provides a technique, based on partially observable Markov decision processes (POMDPs), for building automatic recovery controllers to guide distributed system recovery...
Kaustubh R. Joshi, William H. Sanders, Matti A. Hi...
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...
Nowadays, due to the lack of face-to-face contact, distance course instructors have real difficulties knowing who their students are, how their students behave in the virtual cour...
Skyline queries help users make intelligent decisions over complex data, where different and often conflicting criteria are considered. Current skyline computation methods are rest...
Ping Wu, Caijie Zhang, Ying Feng, Ben Y. Zhao, Div...
Although a partially observable Markov decision process (POMDP) provides an appealing model for problems of planning under uncertainty, exact algorithms for POMDPs are intractable...