Skip to main content
SpringerLink
Log in

CHREST Models of Implicit Learning and Board Game Interpretation

  • Conference paper
Artificial General Intelligence (AGI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7716))

Included in the following conference series:

Abstract

A general theory of intelligence must include learning, the process of converting experiences into retrievable memories. We present two CHREST models to illustrate the effects of learning across two different time scales (minutes and years, respectively). The first is an illustration of implicit learning, checking the validity of strings drawn from an artificial grammar. The second looks at the interpretation of boardgame positions. The same learning and retrieval mechanisms are used in both cases, and we argue that CHREST can be used by an artificial general intelligence to construct and access declarative memory.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
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

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, J.R., Bothell, D., Byrne, M.D., Douglass, S., Lebi‘ere, C., Qin, Y.L.: An integrated theory of the mind. Psychological Review 111(4), 1036–1060 (2004)

    Article  Google Scholar 

  2. Bilalić, M., McLeod, P., Gobet, F.: Specialization effect and its influence on memory and problem solving in expert chess players. Cognitive Science 33, 1117–1143 (2009)

    Article  Google Scholar 

  3. Bossomaier, T., Traish, J., Gobet, F., Lane, P.C.R.: Neuro-cognitive model of move location in the game of Go. In: Proceedings of the 2012 International Joint Conference on Neural Networks (2012)

    Google Scholar 

  4. de Groot, A.D., Gobet, F.: Perception and Memory in Chess: Heuristics of the Professional Eye. Van Gorcum, Assen (1996)

    Google Scholar 

  5. Ericsson, K.A., Charness, N., Feltovich, P.J., Hoffman, R.R.: The Cambridge Handbook of Expertise. CUP, New York (2006)

    Book  Google Scholar 

  6. Evans, J.S.B.T.: Dual-processing accounts of reasoning, judgment and social cognition. Annual Review of Psychology 59, 255–278 (2008)

    Article  Google Scholar 

  7. Freudenthal, D., Pine, J.M., Gobet, F.: Simulating the referential properties of Dutch, German and English root infinitives in MOSAIC. Language Learning and Development 15, 1–29 (2009)

    Article  Google Scholar 

  8. Gobet, F.: A pattern-recognition theory of search inexpert problem solving. Thinking and Reasoning 3, 291–313 (1997)

    Article  Google Scholar 

  9. Gobet, F.: Using a cognitive architecture for addressing the question of cognitive universals in cross-cultural psychology: The example of awalé. Journal of Cross-Cultural Psychology 40, 627–648 (2009)

    Article  Google Scholar 

  10. Gobet, F.: Psychologie du talent et de l’expertise. De Boeck, Bruxelles (2011)

    Google Scholar 

  11. Gobet, F., Lane, P.C.R., Croker, S.J., Cheng, P.C.H., Jones, G., Oliver, I., Pine, J.M.: Chunking mechanisms in human learning. Trends in Cognitive Sciences 5, 236–243 (2001)

    Article  Google Scholar 

  12. Jones, G.A., Gobet, F., Pine, J.M.: Computer simulations of developmental change: The contributions of working memory capacity and long-term knowledge. Cognitive Science 32, 1148–1176 (2008)

    Article  Google Scholar 

  13. Kennedy, W., Patterson, R.: Modeling intuitive decision making in ACT-R. In: Proceedings of the Eleventh International Conference on Computational Modeling, pp. 1–6 (2012)

    Google Scholar 

  14. Laird, J.E.: The Soar Cognitive Architecture. MIT Press (2012)

    Google Scholar 

  15. Lane, P.C.R., Cheng, P.C.H., Gobet, F.: CHREST+: Investigating how humans learn to solve problems with diagrams. AISB Quarterly 103, 24–30 (2000)

    Google Scholar 

  16. Lane, P.C.R., Gobet, F.: Perception in chess and beyond: Commentary on Linhares and Freitas (2010). New Ideas in Psychology 29(2011), 156–161 (2011)

    Article  Google Scholar 

  17. Lane, P.C.R., Gobet, F.: A theory-driven testing methodology for developing scientific software. Journal of Experimental and Theoretical Artificial Intelligence 24, 421–456 (2012)

    Article  Google Scholar 

  18. Lane, P.C.R., Gobet, F.: Using chunks to categorise chess positions. In: Research and Development in Intelligent Systems XXIX: Proceedings of the Thirty-Second SGAI International Conference on Artificial Intelligence. Springer (2012)

    Google Scholar 

  19. Langley, P., Laird, J.E., Rogers, S.: Cognitive architectures: Research issues and challenges. Cognitive Systems Research 10, 141–160 (2009)

    Article  Google Scholar 

  20. Newell, A.: Unified Theories of Cognition. Harvard University Press, Cambridge (1990)

    Google Scholar 

  21. Reber, A.S.: Implicit learning of artificial grammars. Journal of Verbal Learning and Verbal Behaviour 6, 855–863 (1967)

    Article  Google Scholar 

  22. Richman, H.B., Simon, H.A.: Context effects in letter perception: Comparison of two theories. Psychological Review 3, 417–432 (1989)

    Article  Google Scholar 

  23. Schiller, M., Gobet, F.: A comparison between cognitive and AI models of blackjack strategy learning. In: Proceedings of the 35th German Conference on Artificial Intelligence. Springer, New York (2012)

    Google Scholar 

  24. Sloman, S.: The empirical case for two systems of reasoning. Psychological Bulletin 119, 3–22 (1996)

    Article  Google Scholar 

  25. Taatgen, N., Anderson, J.R.: The past, present, and future of cognitive architectures. Topics in Cognitive Science 2, 693–704 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science, University of Hertfordshire, Hatfield, AL10 9AB, UK

    Peter Lane

  2. School of Social Sciences, Brunel University, Uxbridge, UX8 3BH, UK

    Fernand Gobet

Authors
  1. Peter Lane
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fernand Gobet
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Humboldt Universität Berlin, Raumerstr. 11, 10437, Berlin, Germany

    Joscha Bach

  2. Aidyia Ltd., Unit 612, 6/F, Lu Plaza, 2 Wing Yip Street, Kwun Tong, Hong Kong

    Ben Goertzel

  3. Adams State University, Suite 3060, 81101, Alamosa, CO, USA

    Matthew Iklé

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lane, P., Gobet, F. (2012). CHREST Models of Implicit Learning and Board Game Interpretation. In: Bach, J., Goertzel, B., Iklé, M. (eds) Artificial General Intelligence. AGI 2012. Lecture Notes in Computer Science(), vol 7716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35506-6_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35506-6_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35505-9

  • Online ISBN: 978-3-642-35506-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation