We introduce a metaheuristic framework for combinatorial optimization. Our framework is similar to others (e.g. [1]) in that it is modular enough that important components can be i...
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
: This paper analyzes the influence of different parameters of Support Vector Machine (SVM) on text categorization performance. The research is carried out on different text collec...
This work studies optimal sensor placement and motion coordination strategies for mobile sensor networks. For a target tracking application with range sensors, we investigate the ...
This paper introduces a multiagent optimization algorithm inspired by the collective behavior of social insects. In our method, each agent encodes a possible solution of the probl...