Abstract In the controlled ovary hyperstimulation (COH) cycle of the in vitro fertilization-embryo transfer (IVFET) therapy, the clinicians observe the patients' responses to ...
Dynamic programming algorithms provide a basic tool identifying optimal solutions in Markov Decision Processes (MDP). The paper develops a representation for decision diagrams sui...
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
The one-step anticipatory algorithm (1s-AA) is an online algorithm making decisions under uncertainty by ignoring future non-anticipativity constraints. It makes near-optimal decis...
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...