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Modality in the MGLAIR Architecture

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 196)

Abstract

The MGLAIR cognitive agent architecture includes a general model of modality and support for concurrent multimodal perception and action. It provides afferent and efferent modalities as instantiable objects used in agent implementations. Each modality is defined by a set of properties that govern its use and its integration with reasoning and acting. This paper presents the MGLAIR model of modalities and mechanisms for their use in computational cognitive agents.

Keywords

Cognitive Agent Cognitive Architecture Perceptual Structure Knowledge Layer Agent Implementation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Anderson, J.: ACT: A simple theory of complex cognition. American Psychologist 51, 355–365 (1996)CrossRefGoogle Scholar
  2. 2.
    Arrabales, R., Ledezma, A., Sanchis, A.: A Cognitive Approach to Multimodal Attention. Journal of Physical Agents 3(1), 53 (2009)Google Scholar
  3. 3.
    Calvert, G., Spence, C., Stein, B. (eds.): The Handbook of Multisensory Processes. MIT Press (2004)Google Scholar
  4. 4.
    Kieras, D., Meyer, D.: An overview of the EPIC architecture for cognition and performance with application to human-computer interaction. Human-Computer Interaction 12(4), 391–438 (1997)CrossRefGoogle Scholar
  5. 5.
    Kumar, D.: A unified model of acting and inference. In: Nunamaker Jr., J.F., Sprague Jr., R.H. (eds.) Proceedings of the Twenty-Sixth Hawaii International Conference on System Sciences, vol. 3, pp. 483–492. IEEE Computer Society Press, Los Alamitos (1993)CrossRefGoogle Scholar
  6. 6.
    Laird, J.E., Newell, A., Rosenbloom, P.S.: Soar: an architecture for general intelligence. Artif. Intell. 33(1), 1–64 (1987)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Langley, P., Laird, J., Rogers, S.: Cognitive architectures: Research issues and challenges. Cognitive Systems Research 10(2), 141–160 (2009)CrossRefGoogle Scholar
  8. 8.
    Shapiro, S., Anstey, J., Pape, D., Nayak, T., Kandefer, M., Telhan, O.: MGLAIR agents in virtual and other graphical environments. In: Proceedings of the National Conference on Artificial Intelligence, p. 1704. AAAI Press, MIT Press, Menlo Park, Cambridge (1999/2005)Google Scholar
  9. 9.
    Shapiro, S.C., Anstey, J., Pape, D.E., Nayak, T.D., Kandefer, M., Telhan, O.: The Trial The Trail, Act 3: A virtual reality drama using intelligent agents. In: Young, R.M., Laird, J. (eds.) Proceedings of the First Annual Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2005), pp. 157–158. AAAI Press, Menlo Park (2005)Google Scholar
  10. 10.
    Shapiro, S.C., Bona, J.P.: The GLAIR Cognitive Architecture. International Journal of Machine Consciousness 2(2), 307–332 (2010)CrossRefGoogle Scholar
  11. 11.
    Shapiro, S.C., Rapaport, W.J.: The SNePS family. Computers & Mathematics with Applications 23(2-5), 243–275 (1992)MATHCrossRefGoogle Scholar
  12. 12.
    S. C. Shapiro and The SNePS Implementation Group. SNePS 2.7 User’s Manual. Department of Computer Science and Engineering, University at Buffalo, The State University of New York, Buffalo, NY (2007), http://www.cse.buffalo.edu/sneps/Manuals/manual27.pdf
  13. 13.
    Stein, B., Meredith, M.: The Merging of the Senses. The MIT Press (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Computer Science and EngineeringUniversity at BuffaloBuffaloUSA

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