By Ying Tan, Yuhui Shi, Carlos Coello Coello
This booklet and its better half quantity, LNCS vol. 8794 and 8795 represent the lawsuits of the fifth overseas convention on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised complete papers offered have been rigorously reviewed and chosen from 198 submissions. The papers are geared up in 18 cohesive sections, three unique classes and one aggressive consultation protecting all significant subject matters of swarm intelligence examine and improvement resembling novel swarm-based seek equipment; novel optimization set of rules; particle swarm optimization; ant colony optimization for vacationing salesman challenge; synthetic bee colony algorithms; synthetic immune approach; evolutionary algorithms; neural networks and fuzzy tools; hybrid equipment; multi-objective optimization; multi-agent platforms; evolutionary clustering algorithms; type equipment; GPU-based tools; scheduling and course making plans; instant sensor networks; energy approach optimization; swarm intelligence in picture and video processing; functions of swarm intelligence to administration difficulties; swarm intelligence for real-world application.
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Additional info for Advances in Swarm Intelligence: 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I
Indeed, many of these models simulate only homogenous pedestrians. In the reality, there are different personalities. The goal of our work is to reproduce realistic pedestrian crowd simulated situations by simulating a realistic pedestrian behavior. In this context, we proposed, firstly, our HuNAC (Human's Nature of Autonomous Crowds) model . The design of the pedestrian behavior is based on psychosocial and psychophysical studies of normative personalities. In a second time, in order to have more realistic simulation, we opted for the PHuNAC  (Personalities’ Human's Nature of Autonomous Crowds) version which integrates heterogeneous crowd.
Beltaief, S. El Hadouaj, and K. Ghedira Experiments and Discussions To implement our model we used NetLogo. Our experiments consist in comparing real and simulated crowds. Firstly, we present qualitative experiments and then we present quantitative experiments. 1 Qualitative Experiments The most common form of experimental results of crowd simulation systems are animation screen-shots. ) to show scenarios where agents perform a believable swarm behavior. If the visual output seems to exhibit real situations, it is assumed that the system is successful in simulating crowds .
IEEE (2009) 20. : Development of a Miniature Robot for Swarm Robotic Application. International Journal of Computer and Electrical Engineering 1, 436–442 (2009) 21. : Encoderless position estimation and error correction techniques for miniature mobile robots. Turkish Journal of Electrical Engineering & Computer Sciences 21, 1631–1645 (2013) 22. : Development of IR-Based Short-Range Communication Techniques for Swarm Robot Applications. Advances in Electrical and Computer Engineering 10(4), 61–68 (2010) 23.