skip to main content
research-article
Free access

Adaptive computation: the multidisciplinary legacy of John H. Holland

Published: 22 July 2016 Publication History

Abstract

John H. Holland's general theories of adaptive processes apply across biological, cognitive, social, and computational systems.

References

[1]
Arthur, W.B. Holland, J.H., LeBaron, B.D., Palmer, R.G., and Tayler, P. Asset pricing under endogenous expectations in an artificial stock market. In The Economy As an Evolving Complex System II, W.B. Arthur, S. Durlauf, and D. Lane, Eds. Addison-Wesley, Reading, MA, 1997.
[2]
Ashby, W.R. An Introduction to Cybernetics. Chapman & Hall, London, 1956.
[3]
Bellman, R.E. Adaptive Control Processes: A Guided Tour. Princeton University Press, Princeton, NJ, 1961.
[4]
Booker, L.B., Goldberg, D.E., and Holland, J.H. Classifier systems and genetic algorithms. Artificial Intelligence 40, 1--3 (1989), 235--282.
[5]
Christiansen, F.B. and Feldman, M.W. Algorithms, genetics, and populations: The schemata theorem revisited. Complexity 3, 3 (1998), 57--64.
[6]
Dennett, D.C. Elbow Room: The Varieties of Free Will Worth Wanting. MIT Press, Cambridge, MA, 1984.
[7]
Eddington, A. The Nature of the Physical World: Gifford Lectures, 1927. Cambridge University Press, Cambridge, U.K., 1927.
[8]
Fisher, R.A. The Genetical Theory of Natural Selection: A Complete Variorum Edition. Oxford University Press, Oxford, U.K., 1930.
[9]
Goldberg, D.E. Computer-Aided Gas Pipeline Operation Using Genetic Algorithms and Rule Learning. Ph.D. Dissertation, University of Michigan, Ann Arbor, MI, 1983; http://www.worldcat.org/title/computer-aided-gas-pipeline-operation-using-genetic-algorithms-and-rule-learning/oclc/70390568
[10]
Holland, J.H. Outline for a logical theory of adaptive systems. Journal of the ACM 9, 3 (1962), 297--314.
[11]
Holland, J.H. Genetic algorithms and the optimal allocation of trials. SIAM Journal on Computing 2, 2 (1973), 88--105.
[12]
Holland, J.H. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. University of Michigan Press, Ann Arbor, MI, 1975.
[13]
Holland, J.H. Escaping brittleness: The possibilities of general-purpose learning algorithms applied to parallel rule-based systems. In Machine Learning: An Artificial Intelligence Approach, Volume 2, R.S. Michalski, J.G. Carbonell, and T.M. Mitchell, Eds. Morgan-Kaufman, San Francisco, CA, 1986, 593--623.
[14]
Holland, J.H. Induction: Processes of Inference, Learning, and Discovery. MIT Press, Cambridge, MA, 1989.
[15]
Holland, J.H. Genetic algorithms. Scientific American 267 (July 1992), 44--50.
[16]
Holland, J.H. Hidden Order: How Adaptation Builds Complexity. Perseus Books, New York, 1995.
[17]
Holland, J.H. Echoing emergence: Objectives, rough definitions, and speculations for Echo-class models. In Complexity: Metaphor, Models, and Reality, G.A. Cowen, D. Pines, and D. Meltzer, Eds. Perseus Books, New York, 1999, 309--342.
[18]
Holland, J.H. Emergence: From Chaos to Order. Oxford University Press, Oxford, U.K., 2000.
[19]
Holland, J.H. Signals and Boundaries: Building Blocks for Complex Adaptive Systems. MIT Press, Cambridge, MA, 2012.
[20]
Holland, J.H. Complexity: A Very Short Introduction. Oxford University Press, Oxford, U.K., 2014.
[21]
Holland, J.H. and Reitman, J.S. Cognitive systems based on adaptive algorithms. ACM SIGART Bulletin 63 (June 1977), 49.
[22]
Hraber, P.T., Jones, T., and Forrest, S. The ecology of Echo. Artificial Life 3, 3 (1997), 165--190.
[23]
London, R.L. Who Earned First Computer Science Ph.D.? blog@cacm (Jan. 15, 2013); http://cacm.acm.org/blogs/blog-cacm/159591-who-earned-first-computer-science-phd/fulltext
[24]
Palmer, R.G., Arthur, W.B., Holland, J.H., LeBaron, B., and Tayler, P. Artificial economic life: A simple model of a stock market. Physica D: Nonlinear Phenomena 75, 1--3 (1994), 264--274.
[25]
Rochester, N., Holland, J.H., Haibt, L.H., and Duda, W. Tests on a cell assembly theory of the action of the brain, using a large digital computer. IRE Transactions on Information Theory 2, 3 (1956), 80--93.
[26]
Samuel, A.L. Some studies in machine learning using the game of checkers. IBM Journal of Research and Development 3, 3 (1959), 210--229.
[27]
Smith, S.F. A Learning System Based on Genetic Adaptive Algorithms. Ph.D. Dissertation, University of Pittsburgh, Pittsburgh, PA, 1980.
[28]
Sutton, A.G. and Barto, R.S. Time derivative models of Pavlovian reinforcement. In Learning and Computational Neuroscience: Foundations of Adaptive Networks, M. Gabriel and J. Moore, Eds. MIT Press, Cambridge, MA, 1990, 497--537.
[29]
Waldrop, M.M. Complexity: The Emerging Science at the Edge of Order and Chaos. Simon and Schuster, New York, 1993.
[30]
Ziegler, B. Theory of Modeling and Simulation. Wiley Interscience, New York, 1976.

Cited By

View all
  • (2024)Theoretical PrismUnderstanding and Managing Socioeconomic Systems Behaviour10.1007/978-3-031-57057-5_2(9-22)Online publication date: 24-May-2024
  • (2023)Path Planning Technique for Mobile Robots: A ReviewMachines10.3390/machines1110098011:10(980)Online publication date: 23-Oct-2023
  • (2023)Stoichiometric model of a fully closed bioregenerative life support system for autonomous long-duration space missionsFrontiers in Astronomy and Space Sciences10.3389/fspas.2023.119868910Online publication date: 16-Aug-2023
  • Show More Cited By

Index Terms

  1. Adaptive computation: the multidisciplinary legacy of John H. Holland

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image Communications of the ACM
      Communications of the ACM  Volume 59, Issue 8
      August 2016
      94 pages
      ISSN:0001-0782
      EISSN:1557-7317
      DOI:10.1145/2975594
      • Editor:
      • Moshe Y. Vardi
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 22 July 2016
      Published in CACM Volume 59, Issue 8

      Permissions

      Request permissions for this article.

      Check for updates

      Qualifiers

      • Research-article
      • Popular
      • Refereed

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)342
      • Downloads (Last 6 weeks)51
      Reflects downloads up to 17 Feb 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)Theoretical PrismUnderstanding and Managing Socioeconomic Systems Behaviour10.1007/978-3-031-57057-5_2(9-22)Online publication date: 24-May-2024
      • (2023)Path Planning Technique for Mobile Robots: A ReviewMachines10.3390/machines1110098011:10(980)Online publication date: 23-Oct-2023
      • (2023)Stoichiometric model of a fully closed bioregenerative life support system for autonomous long-duration space missionsFrontiers in Astronomy and Space Sciences10.3389/fspas.2023.119868910Online publication date: 16-Aug-2023
      • (2023)Surface roughness R prediction in Selective Laser Melting of 316L stainless steel by means of artificial intelligence inferenceJournal of King Saud University - Engineering Sciences10.1016/j.jksues.2021.03.00235:2(148-156)Online publication date: Feb-2023
      • (2020)Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic AlgorithmSensors10.3390/s2020587320:20(5873)Online publication date: 17-Oct-2020
      • (2019)Assessment of Complex Adaptive System Changeability Using a Learning Classifier SystemIEEE Systems Journal10.1109/JSYST.2018.286762913:3(2177-2188)Online publication date: Sep-2019
      • (2019)Optimization of the allocation of academic schedules through artificial intelligence techniquesJournal of Physics: Conference Series10.1088/1742-6596/1403/1/0120191403(012019)Online publication date: 21-Nov-2019
      • (2018)The Internet of Things and fast data streams: prospects for geospatial data science in emerging information ecosystemsCartography and Geographic Information Science10.1080/15230406.2018.1503973(1-18)Online publication date: 13-Sep-2018
      • (2018)How to learn and how to teach computational thinking: Suggestions based on a review of the literatureComputers & Education10.1016/j.compedu.2018.07.004126(296-310)Online publication date: Nov-2018
      • (2017)The AWA Artificial emergent aWareness Architecture model for Artificial Immune Ecosystems2017 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2017.7969340(403-410)Online publication date: 5-Jun-2017
      • Show More Cited By

      View Options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Digital Edition

      View this article in digital edition.

      Digital Edition

      Magazine Site

      View this article on the magazine site (external)

      Magazine Site

      Login options

      Full Access

      Figures

      Tables

      Media

      Share

      Share

      Share this Publication link

      Share on social media