Stochastic games generalize Markov decision processes MDPs to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards de...
Michael J. Kearns, Yishay Mansour, Satinder P. Sin...
We give an optimal dynamic programming algorithm to solve a class of finite-horizon decentralized Markov decision processes (MDPs). We consider problems with a broadcast informati...
In ergodic MDPs we consider stationary distributions of policies that coincide in all but n states, in which one of two possible actions is chosen. We give conditions and formulas...
ASED ABSTRACTION-REFINEMENT FRAMEWORK FOR MARKOV DECISION PROCESSES Mark Kattenbelt Marta Kwiatkowska Gethin Norman David Parker CL-RR-08-06 Oxford University Computing Laborator...
Mark Kattenbelt, Marta Z. Kwiatkowska, Gethin Norm...
Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead, they are very often dependent and interleaved over time. This is mostly due to uncertainty...