We present a method for modeling user navigation on a web site using grammatical inference of stochastic regular grammars. With this method we achieve better models than the previo...
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
In this paper we describe the initial results of an investigation into the relationship between Markov Decision Processes (MDPs) and Belief-Desire-Intention (BDI) architectures. W...
We propose a learning algorithm for a variable memory length Markov process. Human communication, whether given as text, handwriting, or speech, has multi characteristic time scal...
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...