Download Advances in Computational Intelligence: IEEE World Congress by Piero P. Bonissone (auth.), Jing Liu, Cesare Alippi, PDF

By Piero P. Bonissone (auth.), Jing Liu, Cesare Alippi, Bernadette Bouchon-Meunier, Garrison W. Greenwood, Hussein A. Abbass (eds.)

This cutting-edge survey deals a renewed and clean specialize in the growth in evolutionary computation, in neural networks, and in fuzzy platforms. The ebook offers the services and studies of major researchers spanning a various spectrum of computational intelligence in those parts. the result's a balanced contribution to the learn zone of computational intelligence that are meant to serve the neighborhood not just as a survey and a reference, but additionally as an thought for the longer term development of the state-of-the-art of the sector. The thirteen chosen chapters originate from lectures and displays given on the IEEE international Congress on Computational Intelligence, WCCI 2012, held in Brisbane, Australia, in June 2012.

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Read Online or Download Advances in Computational Intelligence: IEEE World Congress on Computational Intelligence, WCCI 2012, Brisbane, Australia, June 10-15, 2012. Plenary/Invited Lectures PDF

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Extra resources for Advances in Computational Intelligence: IEEE World Congress on Computational Intelligence, WCCI 2012, Brisbane, Australia, June 10-15, 2012. Plenary/Invited Lectures

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Two separate configurations of the robot foraging world are used in the experiments. The first two experiments use a “simple” world where the toroidal surface is 2000 by 2000 units, with a single plant type of value 100 and 50 randomly distributed instances of the plant. In this world, the agents have a straightforward task of learning to navigate efficiently and gather as many plants as possible. The third set of experiments uses both the simple world and a second, more complex world to evaluate performance.

Subcultural agents outperform monocultural agents, converging to a much higher ultimate fitness. The system utilizes a steady-state evolution in which at every timestep each agent probabilistically teaches the lowest-fitness member of the population within some radius, effectively forming geographical subcultures. Figures 6 and 7 show the results of the subcultural ESL algorithm compared to the student-teacher variant of NEW TIES and simple neuroevolution. Subcultural ESL converges to a near-optimal solution faster than the student-teacher variant in both the simple and the complex world.

38 R. Miikkulainen et al. The playing field contains one central obstacle (a wall), four peripheral obstacles (trees), and four walls around the perimeter to contain all agents in the same general area. Each NERO agent starts a battle with 20 hit-points. At each time slice of the simulation, each agent has the opportunity to fire a virtual laser at the closest target on the opponent’s team that is within two degrees of the agent’s current orientation. If an agent fires and hits an opponent, the opponent loses one hit-point.

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