In this paper we consider the problem of policy evaluation in reinforcement learning, i.e., learning the value function of a fixed policy, using the least-squares temporal-differe...
Alessandro Lazaric, Mohammad Ghavamzadeh, Ré...
This book shows how to implement some AI techniques in java such as Search, Reasoning, Semantic Web, Expert Systems, Genetic Algorithms, Neural Networks, Machine Learning with Weka...
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true ...
The goal of this work is the design and construction of adaptive tutorials based on the application of algorithms for the automatic resolution of problems which can be used to aut...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...