Intelligent Distributed Computing III: Proceedings of the by Nicholas R. Jennings, Alex Rogers (auth.), George Angelos

By Nicholas R. Jennings, Alex Rogers (auth.), George Angelos Papadopoulos, Costin Badica (eds.)

This publication represents the peer-reviewed complaints of the 3rd foreign Symposium on clever dispensed Computing – IDC 2009 held in Ayia Napa, Cyprus in the course of October 13-14, 2009.

The 36 contributions during this ebook tackle many subject matters on the topic of thought and purposes of clever disbursed computing, together with: actor-agent platforms, agentbased simulation, autonomic computing, computational provider economies, defeasible reasoning, disbursed info mining, dispensed common sense programming, e-learning, emergent houses in complicated platforms, formal equipment of clever disbursed platforms, genetic and evolutionary algorithms, info retrieval, wisdom fusion, multi-sensor networks, cellular advert hoc networks, cellular computing, ontologies and metadata, peer-to-peer networks, strategy modeling and integration, distant sensing allotted structures, safe e-payment structures, social networks, surveillance and catastrophe administration functions, swarm computing, net prone and systems.

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This MAS has been deployed using the Searchy platform [2]. In this way the experimentation can be divided into different simple operations that are composed and executed in parallel, increasing the performance and the search capability of the algorithm. There are six roles defined in the MAS: control, population, crossover, fitness evaluation, codification and alphabet agent. Each role is implemented using a specialized agent and there are several agents to implement crossover and codification.

The first one is an initial set of experiments whose aim is to select the GA parameters, the results are shown in Table 1. Parameters yield similar optimum values for all the investigated algorithms with one notable exception, the mutation probability. 1 0 0 0 20 40 60 80 100 0 Generations 20 40 60 80 100 Generations (a) Email regex (b) Phone numbers regex Fig. 3 Comparison of codifications in regex evolution. Best individual and average fitness are shown. cut and splice crossover operator (VLG and bmGA cs) have an optimum mutation probability arround one order of magnitude lower than the others algorithms (bmGA with any form of our proposed crossover).

The higher disruptive capabilities of cut and splice operator compared to the proposed crossover operator may explain this difference. A second set of experiments were executed to study the performance of the three described codifications. In order to obtain comparable results, a cut and splice recombination operator has been used in all the experiments belonging to this second experimental stage. The two case studies yield similar experimental results, as can be seen in Fig. 3. Results suggest that plain VLA archieve higher best fitness however Fig.

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