We are interested in building decision-support software for social welfare case managers. Our model in the form of a factored Markov decision process is so complex that a standard...
Growing complexity of the data and processes to be managed, as well as the transition from strict governmental regulation towards autonomy make academic institutions a significant ...
The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact s...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...