We present and evaluate a method for estimating the relevance and calibrating the values of parameters of an evolutionary algorithm. The method provides an information theoretic m...
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Peer-to-peer systems rely on scalable overlay networks that enable efficient routing between its members. Hypercubic topologies facilitate such operations while each node only nee...
A quality-time analysis of multi-objective evolutionary algorithms (MOEAs) based on schema theorem and building blocks hypothesis is developed. A bicriteria OneMax problem, a hypo...
Abstract. Coordination graphs offer a tractable framework for cooperative multiagent decision making by decomposing the global payoff function into a sum of local terms. Each age...