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  • Conference proceedings
  • © 2014

Simulated Evolution and Learning

10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, Proceedings

Editors:

  1. Grant Dick

    1. Otago University, Dunedin, New Zealand

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  2. Will N. Browne

    1. Victoria University of Welling, New Zealand

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  3. Peter Whigham

    1. University of Otago, Dunedin, New Zealand

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  4. Mengjie Zhang

    1. Unitec Institute of Technology, Victoria University of Wellington, New Zealand

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  5. Lam Thu Bui

    1. Le Quy Don Technical University, Hanoi, Vietnam

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  6. Hisao Ishibuchi

    1. Department of Computer Science and Intelligent Systems, Graduate School of Engineering, Osaka Prefecture University, Sakai, Japan

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  7. Yaochu Jin

    1. Department of Computing, University of Surrey, Guildford, UK

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  8. Xiaodong Li

    1. RMIT University, Melbourne, Australia

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  9. Yuhui Shi

    1. Department of Electrical & Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

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  10. Pramod Singh

    1. Indian Institute of Information Technology and Management, Gwalior, India

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  11. Kay Chen Tan

    1. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

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  12. Ke Tang

    1. USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), School of Computer Science and Technology, University of Science and Technology of China, Hefei, China

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8886)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Conference series link(s): SEAL: International Conference on Simulated Evolution and Learning

Conference proceedings info: SEAL 2014.

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Table of contents (71 papers)

  1. Evolutionary Multi-objective Optimization

    1. A Multi-Objective A* Search Based on Non-dominated Sorting

      • Mohammad Haqqani, Xiaodong Li, Xinghuo Yu
      Pages 228-238

    2. Extending AεSεH from Many-objective to Multi-objective Optimization

      • Hernán Aguirre, Yuki Yazawa, Akira Oyama, Kiyoshi Tanaka
      Pages 239-250

    3. User Preferences for Approximation-Guided Multi-objective Evolution

      • Anh Quang Nguyen, Markus Wagner, Frank Neumann
      Pages 251-262

  2. Evolutionary Machine Learning

    2. Schemata Bandits for Binary Encoded Combinatorial Optimisation Problems

      • Madalina M. Drugan, Pedro Isasi, Bernard Manderick
      Pages 299-310

    3. Anomaly Detection Using Replicator Neural Networks Trained on Examples of One Class

      • Hoang Anh Dau, Vic Ciesielski, Andy Song
      Pages 311-322

    5. Genetic Programming for Multiclass Texture Classification Using a Small Number of Instances

      • Harith Al-Sahaf, Mengjie Zhang, Mark Johnston
      Pages 335-346

    6. A Stepwise Multi-centroid Classification Learning Algorithm with GPU Implementation

      • Cain Cresswell-Miley, Kourosh Neshatian
      Pages 347-358

    8. Learning Patterns of States in Time Series by Genetic Programming

      • Feng Xie, Andy Song, Vic Ciesielski
      Pages 371-382

    9. Reusing Learned Functionality to Address Complex Boolean Functions

      • Isidro M. Alvarez, Will N. Browne, Mengjie Zhang
      Pages 383-394

  3. Theoretical Developments

    2. Beyond the Edge of Feasibility: Analysis of Bottlenecks

      • Mohammad Reza Bonyadi, Zbigniew Michalewicz, Markus Wagner
      Pages 431-442

    3. Adaptive Risk Aversion in Social Dilemmas

      • Michael Kirley, Friedrich Burkhard von der Osten
      Pages 443-454

    4. Fitness Landscape Analysis of Circles in a Square Packing Problems

      • Rachael Morgan, Marcus Gallagher
      Pages 455-466
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Other Volumes

  1. Simulated Evolution and Learning

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About this book

This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.
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Keywords

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Editors and Affiliations

  • Otago University, Dunedin, New Zealand

    Grant Dick

  • Victoria University of Welling, New Zealand

    Will N. Browne

  • University of Otago, Dunedin, New Zealand

    Peter Whigham

  • Unitec Institute of Technology, Victoria University of Wellington, New Zealand

    Mengjie Zhang

  • Le Quy Don Technical University, Hanoi, Vietnam

    Lam Thu Bui

  • Department of Computer Science and Intelligent Systems, Graduate School of Engineering, Osaka Prefecture University, Sakai, Japan

    Hisao Ishibuchi

  • Department of Computing, University of Surrey, Guildford, UK

    Yaochu Jin

  • RMIT University, Melbourne, Australia

    Xiaodong Li

  • Department of Electrical & Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  • Indian Institute of Information Technology and Management, Gwalior, India

    Pramod Singh

  • Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Kay Chen Tan

  • USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), School of Computer Science and Technology, University of Science and Technology of China, Hefei, China

    Ke Tang

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Bibliographic Information

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Buy it now

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

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