We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
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...
Bounded parameter Markov Decision Processes (BMDPs) address the issue of dealing with uncertainty in the parameters of a Markov Decision Process (MDP). Unlike the case of an MDP, t...
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...