This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prog...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
We present a Mutation-based Validation Paradigm (MVP) technology that can handle complete high-level microprocessor implementations and is based on explicit design error modeling, ...
We consider the problem of planning in a stochastic and discounted environment with a limited numerical budget. More precisely, we investigate strategies exploring the set of poss...