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 specialise in the growth in evolutionary computation, in neural networks, and in fuzzy platforms. The e-book provides 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 examine quarter of computational intelligence that are supposed to serve the neighborhood not just as a survey and a reference, but additionally as an notion for the long run development of the state-of-the-art of the sector. The thirteen chosen chapters originate from lectures and displays given on the IEEE global Congress on Computational Intelligence, WCCI 2012, held in Brisbane, Australia, in June 2012.
Read 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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Additional info for Advances in Computational Intelligence: IEEE World Congress on Computational Intelligence, WCCI 2012, Brisbane, Australia, June 10-15, 2012. Plenary/Invited Lectures
For the battle task, two teams—each consisting of 50 NERO agents—occupy a continuous, two-dimensional, virtual playing ﬁeld of ﬁxed size (see Figure 8). 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.
Pr. (2001) 5. : Machiavellian Intelligence: Social Expertise and the Evolution of Intellect in Monkeys, Apes, and Humans. Oxford University Press, USA (1989) 6. : Collective behavior of interacting self-propelled particles. Physica A 281, 17–29 (2000) 7. : Incremental social learning in particle swarms. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 41(2), 368–384 (2011) 8. : Cultural evolution in a population of neural networks. , Tagliaferri, R. ) Neural Nets Wirn 1996, pp.
The third set of experiments uses both the simple world and a second, more complex world to evaluate performance. The “complex” world has a surface of 500 by 500 units, with ﬁve diﬀerent plant types of value -100, -50, 0, 50, and 100. For each plant type, 20 instances are created and randomly distributed across the surface. This world presents the agents with a more diﬃcult task as they must eﬃciently gather nutritious food while simultaneously avoiding the poisonous food. In all four experiments, 100 diﬀerent agents are created in each generation.