Knowledge-Free and Learning-Based Methods in Intelligent Game Playing

  • Jacek Mańdziuk

Part of the Studies in Computational Intelligence book series (SCI, volume 276)

Table of contents

  1. Front Matter
  2. Introduction

    1. Jacek Mańdziuk
      Pages 1-7
  3. Part I: AI Tools and State-of-the-Art Accomplishments in Mind Games

    1. Front Matter
      Pages 9-9
    2. Jacek Mańdziuk
      Pages 15-39
    3. Jacek Mańdziuk
      Pages 41-50
  4. Part II: CI Methods in Mind Games. Towards Human-Like Playing

    1. Front Matter
      Pages 51-51
    2. Jacek Mańdziuk
      Pages 71-89
  5. Part III: An Overview of Challenges and Open Problems

    1. Front Matter
      Pages 91-91
    2. Jacek Mańdziuk
      Pages 93-97
    3. Jacek Mańdziuk
      Pages 99-119
    4. Jacek Mańdziuk
      Pages 121-153
    5. Jacek Mańdziuk
      Pages 155-168
  6. Part IV: Grand Challenges

    1. Front Matter
      Pages 181-181
    2. Jacek Mańdziuk
      Pages 183-204
    3. Jacek Mańdziuk
      Pages 205-214
    4. Jacek Mańdziuk
      Pages 215-229
    5. Jacek Mańdziuk
      Pages 231-234
  7. Back Matter

About this book


The book is focused on the developments and prospective challenging problems in the area of mind game playing (i.e. playing games that require mental skills) using Computational Intelligence (CI) methods, mainly neural networks, genetic/evolutionary programming and reinforcement learning. The majority of discussed game playing ideas were selected based on their functional similarity to human game playing. These similarities include: learning from scratch, autonomous experience-based improvement and example-based learning. The above features determine the major distinction between CI and traditional AI methods relying mostly on using effective game tree search algorithms, carefully tuned hand-crafted evaluation functions or hardware-based brute-force methods.

On the other hand, it should be noted that the aim of this book is by no means to underestimate the achievements of traditional AI methods in game playing domain. On the contrary, the accomplishments of AI approaches are undisputable and speak for themselves. The goal is rather to express my belief that other alternative ways of developing mind game playing machines are possible and urgently needed.


artificial intelligence computational intelligence evolution knowledge knowledge discovery learning modeling neural network reinforcement learning

Authors and affiliations

  • Jacek Mańdziuk
    • 1
  1. 1.Faculty of Mathematics and Information ScienceWarsaw University of TechnologyWarsawPoland

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-642-11677-3
  • Online ISBN 978-3-642-11678-0
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site