Titlebook: Stochastic Switching Systems; Analysis and Design El-Kébir Boukas Book 2006 Birkhäuser Boston 2006 Analysis.Markov.communication.filtering

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egy and multi-chaotic dynamics driving the selection of indices in Differential Evolution (DE). The novelty of the paper is given by the experiments with the multi-chaos-driven adaptive DE concept inside adaptive parameter adjusting DE strategies. These experiments are representing the investigation

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. However, the literature shows that in this area, one is still unable to generate robots that perform better than conventional manual designs, even for simple tasks. It is noted that the main hindrance to satisfactory evolution is poor controller generated as a result of the simultaneous variation

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rameters of an algorithm on the basis of a ‘training set’ of problem instances. There is much interest (but little research so far) on the relationship between the training set and generalization performance. In general terms, we expect that, if an algorithm is targeted at problems of a certain type

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ons. We introduce a model of local repulsion between the walkers and visited sites in order to minimize the waste of steps in revisiting sites, thereby also the cover time. We particularly perform numerical simulations for the case of two colored random walkers (. = 2), namely Ray and Ben, on a squa

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ansportation problem by Hitchcock (1941), Kantorovich (1942) and Koopmans (1949), and (2) an analogue of Kirchhoff’s law of electric circuits by Enke (1951). Samuelson (1952) showed that the Enke problem could be converted into a mathematical programming model. In 1964 Takayama and Judge reformulate

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