Skip to main content
SpringerLink
Log in

Propositional Reasoning for an Embodied Cognitive Model

  • Conference paper
Advances in Artificial Intelligence – SBIA 2004 (SBIA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3171))

Included in the following conference series:

  • 2647 Accesses

Abstract

In this paper we describe the learning and reasoning mechanisms of a cognitive model based on the systemic approach and on the autopoiesis theory. These mechanisms assume perception and action capabilities that can be captured through propositional symbols and uses logic for representing environment knowledge. The logical theories are represented by their conjunctive and disjunctive normal forms. These representations are enriched to contain annotations that explicitly store the relationship among the literals and (dual) clauses in both forms. Based on this representation, algorithms are presented that learn a theory from the agent’s experiences in the environment and that are able to determine the robustness degree of the theories given an assignment representing the environment state.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Bibel, W.: Let’s plan it deductively. In: Proceedings of IJCAI, Nagoya, Japan, August 23-29, vol. 15, pp. 1549–1562. Morgan Kaufmann, San Francisco (1997) (ISBN 1-55860-480-4)

    Google Scholar 

  2. Bittencourt, G.: In the quest of the missing link. In: Proceedings of IJCAI, Nagoya, Japan, August 23-29, vol. 15, pp. 310–315. Morgan Kaufmann, San Francisco (1997) (ISBN 1-55860-480-4)

    Google Scholar 

  3. Bittencourt, G., Marchi, J.: A syntactic approach to satisfaction. In: Konev, B., Schmidt, R. (eds.) Proceedings of the 4th International Workshop on the Implementation of Logics, University of Liverpool and University of Manchester, pp. 18–32 (2003)

    Google Scholar 

  4. Bittencourt, G., Perrussel, L., Marchi, J.: A syntactical approach to revision. Accepted to ECAI 2004

    Google Scholar 

  5. Bittencourt, G., Tonin, I.: An algorithm for dual transformation in first-order logic. Journal of Automated Reasoning 27(4), 353–389 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  6. Brooks, R.A.: Intelligence without representation. Artificial Intelligence (Special Volume Foundations of Artificial Intelligence) 47(1-3), 139–159 (1991)

    Google Scholar 

  7. Damasio, A.R.: Descartes’ Error: Emotion, Reason, and the Human Brain. G.P. Putnam’s Sons, New York (1994)

    Google Scholar 

  8. Darwiche, A., Marquis, P.: A perspective on knowledge compilation. IJCAI, 175–182 (2001)

    Google Scholar 

  9. Fitting, M.: First-Order Logic and Automated Theorem Proving. Springer, New York (1990)

    MATH  Google Scholar 

  10. Ginsberg, M.L., Parkes, A.J., Roy, A.: Supermodels and robustness. In: Proceedings of AAAI 1998, pp. 334–339 (1998)

    Google Scholar 

  11. Kaelbling, L.P., Littman, M.L., Moore, A.W.: Reinforcement learning: A survey. Journal of Artificial Intelligence Research 4, 237–285 (1996)

    Google Scholar 

  12. Kean, A., Tsiknis, G.: An incremental method for generating prime implicants/implicates. Journal of Symbolic Computation 9, 185–206 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  13. Lespérance, Y., Levesque, H.J., Lin, F., Marcu, D., Reiter, R., Scherl, R.B.: A logical approach to high level robot programming – a progress report. In: Kuipers, B. (ed.) Working notes of the 1994 AAAI fall symposium on Control of the Physical World by Intelligent Systems, New Orleans, LA (November 1994)

    Google Scholar 

  14. Levesque, H., Pirri, F., Reiter, R.: Foundations for the situation calculus (1998)

    Google Scholar 

  15. Maturana, H.R., Varela, F.J.: Autopoiesis and cognition: The realization of the living. In: Cohen, R.S., Wartofsky, M.W. (eds.) Boston Studies in the Philosophy of Science, vol. 42, D. Reidel Publishing Co., Dordecht, Holland (1980)

    Google Scholar 

  16. Morin, E.: La Méthode 4, Les Idées. Editions du Seuil, Paris (1991)

    Google Scholar 

  17. Murray, N., Ramesh, A., Rosenthal, E.: The semi-resolution inference rule and prime implicate computations. In: Proc. Fourth Golden West International Conference on Intelligent Systems, San Fransisco, CA, USA, pp. 153–158 (1995)

    Google Scholar 

  18. Newell, A.: The knowledge level. Artificial Intelligence 18, 87–127 (1982)

    Article  Google Scholar 

  19. Parkes, J.: Clustering at the phase transition. In: AAAI/IAAI, pp. 340–345 (1997)

    Google Scholar 

  20. Ramesh, A., Becker, G., Murray, N.V.: CNF and DNF considered harmful for computing prime implicants/implicates. Journal of Automated Reasoning 18(3), 337–356 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  21. Scherl, R., Levesque, H.J.: Knowledge, action, and the frame problem. Artificial Intelligence 1(144), 1–39 (2003)

    Article  MathSciNet  Google Scholar 

  22. Shanahan, M.: Explanation in the situation calculus. In: Bajcsy, R. (ed.) Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, San Mateo, California, pp. 160–165. Morgan Kaufmann, San Francisco (1993)

    Google Scholar 

  23. Slagle, J.R., Chang, C.L., Lee, R.C.T.: A new algorithm for generating prime implicants. IEEE Transactions on Computing 19(4), 304–310 (1970)

    Article  MATH  MathSciNet  Google Scholar 

  24. Socher, R.: Optimizing the clausal normal form transformation. Journal of Automated Reasoning 7(3), 325–336 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  25. Varela, F.J.: Autonomie et Connaissance: Essai sur le Vivant. Editions du Seuil, Paris (1989)

    Google Scholar 

  26. Zhang, L., Malik, S.: The quest for efficient boolean satisfiability solvers. In: Proceedings of 8th International Conference on Computer Aided Deduction(CADE 2002) (invited Paper)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departamento de Automação e Sistemas, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, SC, Brazil

    Jerusa Marchi & Guilherme Bittencourt

Authors
  1. Jerusa Marchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guilherme Bittencourt
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Instituto de Informática, UFRGS, Porto Alegre, RS, Brasil

    Ana L. C. Bazzan

  2. Intelligent Systems Laboratory LSI, Center of Technology, Federal University of Maranao UFMA, Bacanga Campus, 65080-040, Sao Luis, MA, Brazil

    Sofiane Labidi

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Marchi, J., Bittencourt, G. (2004). Propositional Reasoning for an Embodied Cognitive Model. In: Bazzan, A.L.C., Labidi, S. (eds) Advances in Artificial Intelligence – SBIA 2004. SBIA 2004. Lecture Notes in Computer Science(), vol 3171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28645-5_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-28645-5_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23237-7

  • Online ISBN: 978-3-540-28645-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation