Skip to main content
SpringerLink
Log in

Oppositional Concepts in Computational Intelligence

  • Book
  • © 2008

Overview

Editors:
  1. Hamid R. Tizhoosh
    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Mario Ventresca
    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Describes and presents opposition-based computing and concepts

Part of the book series: Studies in Computational Intelligence (SCI, volume 155)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 149.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 199.99
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

Licence this eBook for your library

Institutional subscriptions

Table of contents (14 chapters)

  1. Front Matter

    Download chapter PDF

  2. Introduction

    1. Introduction

      • H. R. Tizhoosh, Mario Ventresca
      Pages 1-8

  3. Part I: Motivations and Theory

    1. Front Matter

      Pages 9-9
      Download chapter PDF

    2. Opposition-Based Computing

      • H. R. Tizhoosh, Mario Ventresca, Shahryar Rahnamayan
      Pages 11-28

    3. Antithetic and Negatively Associated Random Variables and Function Maximization

      • Don L. McLeish
      Pages 29-44

    4. Opposition and Circularity

      • Florencio G. Asenjo
      Pages 45-57

  4. Part II: Search and Reasoning

    1. Front Matter

      Pages 59-59
      Download chapter PDF

    2. Collaborative vs. Conflicting Learning, Evolution and Argumentation

      • Luís Moniz Pereira, Alexandre Miguel Pinto
      Pages 61-89

    3. Proof-Number Search and Its Variants

      • H. Jaap van den Herik, Mark H. M. Winands
      Pages 91-118

  5. Part III: Optimization

    1. Front Matter

      Pages 119-119
      Download chapter PDF

    2. Improving the Exploration Ability of Ant-Based Algorithms

      • Alice Ralickas Malisia
      Pages 121-142

    3. Differential Evolution Via Exploiting Opposite Populations

      • Shahryar Rahnamayan, H. R. Tizhoosh
      Pages 143-160

    4. Evolving Opposition-Based Pareto Solutions: Multiobjective Optimization Using Competitive Coevolution

      • Tse Guan Tan, Jason Teo
      Pages 161-206

  6. Part IV: Learning

    1. Front Matter

      Pages 207-207
      Download chapter PDF

    2. Bayesian Ying-Yang Harmony Learning for Local Factor Analysis: A Comparative Investigation

      • Lei Shi
      Pages 209-232

    3. The Concept of Opposition and Its Use in Q-Learning and Q(λ) Techniques

      • Maryam Shokri, H. R. Tizhoosh, Mohamed S. Kamel
      Pages 233-253

    4. Two Frameworks for Improving Gradient-Based Learning Algorithms

      • Mario Ventresca, H. R. Tizhoosh
      Pages 255-284

  7. Part V: Real World Applications

    1. Front Matter

      Pages 285-285
      Download chapter PDF

    2. Opposite Actions in Reinforced Image Segmentation

      • Farhang Sahba, H. R. Tizhoosh
      Pages 287-297

    3. Opposition Mining in Reservoir Management

      • Masoud Mahootchi, H. R. Tizhoosh, Kumaraswamy Ponnambalam
      Pages 299-321
Back to top

Keywords

About this book

“Theoppositeofacorrectstatementisafalsestatement.Buttheopposite of a profound truth may well be another profound truth.” – Niels Bohr This volume is motivated in part by the observation that opposites permeate everything around us, in some form or another. Its study has attracted the attention of countless minds for at least 2500 years. However, due to the lack of an accepted mathematical formalism for opposition it has not been explicitly studiedtoanygreatlengthin?eldsoutsideofphilosophyandlogic.This,despite the fact that we observe opposition everywhere in nature, our minds seem to divide the world into entities and opposite entities; indeed we use opposition everyday. We have become so accustomed to opposition that its existence is accepted, not usually questioned and its importance is constantly overlooked. On one hand, this volume is a ?st attempt to bring together researchers who are inquiring into the complementary nature of systems and processes and, on the other hand, provide some elementary components for a framework to establish a formalism for opposition-based computing. From a computational intelligence perspective, many successful opposition-based concepts have been in existence for a long time. It is not our intention to recast these existing methods, rather to elucidate that, while diverse, they all share the commonality of opposition - in one form or another, either implicitly or explicitly. To this end, we have attempted to provide rough guidelines to understand what makes concepts “oppositional”.

Bibliographic Information

  • Book Title: Oppositional Concepts in Computational Intelligence

  • Editors: Hamid R. Tizhoosh, Mario Ventresca

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-540-70829-2

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2008

  • Hardcover ISBN: 978-3-540-70826-1Due: 02 September 2008

  • Softcover ISBN: 978-3-642-08978-7Published: 28 October 2010

  • eBook ISBN: 978-3-540-70829-2Published: 08 September 2008

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XII, 328

  • Number of Illustrations: 72 b/w illustrations

  • Topics: Mathematical and Computational Engineering, Artificial Intelligence

Publish with us

Policies and ethics

Back to top

Search

Navigation