In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
This paper introduces a novel algorithm for biological sequence compression that makes use of both statistical properties and repetition within sequences. A panel of experts is ma...
Minh Duc Cao, Trevor I. Dix, Lloyd Allison, Chris ...
We propose Genetic Algorithms to improve the feature subset selection by combining the valuable outcomes from multiple feature selection methods. This paper also motivates the use...
Abstract— Meta-learning helps us find solutions to computational intelligence (CI) challenges in automated way. Metalearning algorithm presented in this paper is universal and m...
The integration of different wireless access technologies combined with the huge characteristic diversity of supported services in next-generation systems creates a real heterogen...