Automated rule induction procedures like machine learning and statistical techniques result in rules that lack generalization and maintainability. Developing rules manually throug...
Based on the framework of parameterized complexity theory, we derive tight lower bounds on the computational complexity for a number of well-known NP-hard problems. We start by pr...
Jianer Chen, Benny Chor, Mike Fellows, Xiuzhen Hua...
This paper analyzes the scalability of the population size required in XCS to maintain niches that are infrequently activated. Facetwise models have been developed to predict the ...
Albert Orriols-Puig, David E. Goldberg, Kumara Sas...
Higher integration densities, smaller feature lengths, and other technology advances, as well as architectural evolution, have made microprocessor cores exceptionally complex. Cur...
We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents operating in multi-agent environments. We use the...