This paper explores what kind of user simulation model is suitable for developing a training corpus for using Markov Decision Processes (MDPs) to automatically learn dialog strate...
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...
Researchers often express probabilistic planning problems as Markov decision process models and then maximize the expected total reward. However, it is often rational to maximize ...
We describe a Markov state model for a cloned potassium channel of the human heart ( 1KvLQTI ). The parameters of the model are determined by a least-squares fit of predicted vs. ...
John L. Maryak, Richard H. Smith, Raimond L. Winsl...
Monitoring plan preconditions can allow for replanning when a precondition fails, generally far in advance of the point in the plan where the precondition is relevant. However, mo...