This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of...
The study of belief change has been an active area in philosophy and AI.In recent years two special cases ofbelief change, belief revision and belief update, have been studied in ...
Constraint satisfaction consistency preprocessing methods are used to reduce search e ort. Time and especially space costs limit the amount of preprocessing that will be cost e ec...
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
This article shows how rational analysis can be used to minimize learning cost for a general class of statistical learning problems. We discuss the factors that influence learning...