A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
In order to assist a power plant operator to face unusual situations, we have developed an intelligent assistant that explains the suggested commands generated by an MDP-based pla...
Francisco Elizalde, Luis Enrique Sucar, Alberto Re...
Planning by forward chaining through the world space has long been dismissed as being "obviously" infeasible. Nevertheless, this approach to planning has many advantages...
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...
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...