Skip to main content
SpringerLink
Log in

A Statechart Framework for Agent Roles that Captures Expertise and Learns Improved Behavior

  • Conference paper
Formal Approaches to Agent-Based Systems (FAABS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2699))

Included in the following conference series:

Abstract

We present work in progress that addresses a formalism and a system for computationally modeling human behavior where humans collaborate and communicate with other humans or automated systems with significant problem-solving ability. We conceptualize the simulated participants as agents. The fundamental notion is that of a role. An agent may assume one or more roles, and optimization measures are associated with roles. To represent coordination explicitly, we use an adaptation of Pazzi’s Part-Whole Statecharts, which encapsulate coordination behavior. We include violation transitions to capture non-ideal behavior and violation states for repair. Fuzzy logic control is added to handle large domains and to resolve nondeterminism. A Statechart is represented internally with weighted rules, and an XCS classifier system is used to update the rule base in light of the outcomes of simulations; this provides a form of machine learning.

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. Mosley, K., Esterline, A.: Modeling Societies of Agents and Users Using CSP. In: Proc. 5th World Multi-Conference on Systems, Cybernetics and Informatics (SCI 2001), Orlando, Fl (2001)

    Google Scholar 

  2. Turner, R.: Adaptive Reasoning for Real-World Problems: A Schema-Based Approach. Lawrence Erlbaum Associates, Inc., Hillsdale (1994)

    Google Scholar 

  3. Harel, D.: Statecharts: A Visual Formalism for Complex Systems. Science of Computer Programming 8, 231–274 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  4. Pazzi, L.: Extending statecharts for representing parts and wholes. In: Proceedings of the 23rd EUROMICRO Conference (1997)

    Google Scholar 

  5. Homaifar, A., Hawari, H., Esterline, A.: Application of Biofunctional Learning and Remembering for Multi-Agent Goal Tracking. In: Proc. of SMC 2001 (2001)

    Google Scholar 

  6. Harel, D., Pnueli, A., Schmidt, J.P., Sherman, R.: On the Formal Semantics of Statecharts. In: Proc. 2nd IEEE Symposium on Logic in Computer Science, pp. 54–64 (1987)

    Google Scholar 

  7. Wilson, S.W.: State of XCS Classifier System Research. Technical Report No. 99.1.1, Prediction Dynamics, Concord MA (1999)

    Google Scholar 

  8. VanLehn, K., et al.: Fading and Deepening: The Next Steps for Andes and Other Model- Tracing Tutors. In: Gauthier, G., VanLehn, K., Frasson, C. (eds.) ITS 2000. LNCS, vol. 1839, p. 474. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  9. Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994)

    MATH  Google Scholar 

  10. Iran-Nejad, A., Marsh, E.G.: The figure and the ground of constructive brain functioning: beyond explicit memory processes. Educational Psychologist 7(4), 473–492 (1992)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Electrical Engineering and NASA ACIT Center, North Carolina A&T State University, Greensboro, NC, 27411, USA

    Bahram Kimiaghalam & Abdollah Homaifar

  2. Dept. of Computer Science and NASA ACIT Center, North Carolina A&T State University, Greensboro, NC, 27411, USA

    Albert C. Esterline

Authors
  1. Bahram Kimiaghalam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abdollah Homaifar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Albert C. Esterline
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, Loyola College in Maryland, MD 21210, Baltimore, USA

    Michael G. Hinchey

  2. Advanced Architectures and Automation Branch, NASA Goddard Space Flight Center, MD 20771, Greenbelt, USA

    James L. Rash

  3. NASA Goddard Space Flight Center, MD 20771, Greenbelt, USA

    Walter F. Truszkowski

  4. Advanced Technology Laboratories, Lockheed Martin Corporation, VA 22203, Arlington, USA

    Christopher Rouff

  5. Computer Science Department, University ofWyoming, WY 82070, Laramie, USA

    Diana Gordon-Spears

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kimiaghalam, B., Homaifar, A., Esterline, A.C. (2003). A Statechart Framework for Agent Roles that Captures Expertise and Learns Improved Behavior. In: Hinchey, M.G., Rash, J.L., Truszkowski, W.F., Rouff, C., Gordon-Spears, D. (eds) Formal Approaches to Agent-Based Systems. FAABS 2002. Lecture Notes in Computer Science(), vol 2699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45133-4_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-45133-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40665-5

  • Online ISBN: 978-3-540-45133-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation