—In this paper we develop an adaptive learning algorithm which is approximately optimal for an opportunistic spectrum access (OSA) problem with polynomial complexity. In this OSA...
Typical methods in CRM marketing include action selection on the basis of Markov Decision Processes with fixed transition probabilities on the one hand, and scoring customers separ...
—Understanding of player behaviors is an important issue to keep online games interesting to their players. Focusing on player movement, in our previous work, we proposed a metho...
When modeling real-world decision-theoretic planning problems in the Markov decision process (MDP) framework, it is often impossible to obtain a completely accurate estimate of tr...
Karina Valdivia Delgado, Scott Sanner, Leliane Nun...
We extend qualitative reasoning with estimations of the relative likelihoods of the pos sible qualitative behaviors . We estimate the likelihoods by viewing the dynamics o f a sys...
In part of speech tagging by Hidden Markov Model, a statistical model is used to assign grammatical categories to words in a text. Early work in the field relied on a corpus which...
Spike sorting involves clustering spike trains recorded by a microelectrode according to the source neuron. It is a complicated problem, which requires a lot of human labor, partl...
— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
In this paper, we consider the problem of calculating the signal and transition probabilities of the internal nodes of the combinational logic part of a nite state machine (FSM). ...