Simulated Evolution and Learning

Simulated Evolution and Learning

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Weareverydelightedto presentthis LNCS volume, the proceedingsoftheSixth International Conference on Simulated Evolution And Learning (SEAL 2006). SEALisaprestigiousinternationalconferenceseriesinevolutionarycomputation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), and Busan, Korea (2004). SEAL2006receivedarecord420papersubmissionsthisyear.After anext- sive peer review process involving more than 1100 reviews, the best 117 papers were selected by the programme committee to be presented at the conference and included in this volume, resulting in an acceptance rate of less than 30%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionary learning to evolutionary optimisation, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world. The conference featured four distinguished keynote speakers: Karl Sigmund, Zbigniew Michalewicz, Han La Poutr I e and Gary Yen. Karl Sigmunda€™s talk was on a€œThe Evolution of Cooperation in Groups.a€ Zbigniew Michalewicza€™s talk was on a€œAdaptive Business Intelligence.a€ Han La Poutr I ea€™s talk was on a€œLearning Agents in Socio-economicGames.a€ Gary G. Yena€™s talk was on a€œAdaptive Critics for Fault Tolerant Controla€. We were very fortunate to have such distinguished speakers giving talks at SEAL 2006 despite their busy schedules. Their presence at the conference was yet another indicator of the importance of SEAL on the international research map.This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal ... areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal ... of ISO standard, which consist of 4 code groups such as shipping company codes, container serial codes, check digit codes and container type codes [1][2].

Title:Simulated Evolution and Learning
Author:Tzai-Der Wang
Publisher:Springer Science & Business Media - 2006-10-06


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