This paper proposes an evolutionary framework where a network service is created from a group of autonomous agents that interact and evolve. Agents in our framework are capable of ...
Abstract. Evolutionary Algorithms (EAs) are population-based randomized optimizers often solving problems quite successfully. Here, the focus is on the possible effects of changin...
Abstract. We present upper bounds on the time and space complexity of finding the global optimum of additively separable functions, a class of functions that has been studied exten...
Abstract. When direct measurement of model parameters is not possible, these need to be inferred indirectly from calibration data. To solve this inverse problem, an algorithm that ...
We analyse the probability 1 − δ to be in an optimum solution after k steps of an inhomogeneous Markov chain which is specified by a logarithmic cooling schedule c(k) = Γ/ ln ...