Skip to main content

The Behavior-Oriented Design of Modular Agent Intelligence

  • Conference paper
  • First Online:
Agent Technologies, Infrastructures, Tools, and Applications for E-Services (NODe 2002)

Abstract

Behavior-Oriented Design (BOD) is a development methodology for creating complex, complete agents such as virtual-reality characters, autonomous robots, intelligent tutors or intelligent environments. BOD agents are modular, but not multi-agent systems. They use hierarchical reactive plans to perform ar-bitration between their component modules. BOD provides not only architectural specifications for modules and plans, but a methodology for building them. The BOD methodology is cyclic, consisting of rules for an initial decomposition and heuristics for revising the specification over the process of development.

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

Access this chapter

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. FIPA-OS: A component-based toolkit enabling rapid development of fipa compliant agents. http://fipa-os.sourceforge.net.

  2. Arkin, R. C. (1998). Behavior-Based Robotics. MIT Press, Cambridge, MA.

    Google Scholar 

  3. Ballin,6D. (2000). Special issue: Intelligent virtual agents. Virtual Reality, 5(2).

    Google Scholar 

  4. Bertolini,6D., Busetta, P., Molani, A., Nori, M., and Perini, A. (2002). Designing peer-to-peer applications: an agent-oriented approach. In this volume.

    Google Scholar 

  5. Blumberg, B. M. (1996). Old Tricks, New Dogs: Ethology and Interactive Creatures. PhD thesis, MIT. Media Laboratory, Learning and Common Sense Section.

    Google Scholar 

  6. Boehm, B. W. (1986). A spiral model of software development and enhancement. ACM SIGSOFT Software Engineering Notes, 11(4):22–32.

    Article  Google Scholar 

  7. Brooks, R. A. (1986). A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, RA-2:14–23.

    MathSciNet  Google Scholar 

  8. Bryson, J. J. (2000). Hierarchy and sequence vs. full parallelism in reactive action selection architectures. In From Animals to Animats 6 (SAB00), pages 147–156, Cambridge, MA. MIT Press.

    Google Scholar 

  9. Bryson, J. J. (2001). Intelligence by Design: Principles of Modularity and Coordination for Engineering Complex Adaptive Agents. PhD thesis, MIT, Department of EECS, Cambridge, MA. AI Technical Report 2001-003.

    Google Scholar 

  10. Bryson, J. J. and McGonigle, B. (1998). Agent architecture as object oriented design. In Singh, M. P., Rao, A. S., and Wooldridge, M. J., editors, The Fourth International Workshop on Agent Theories, Architectures, and Languages (ATAL97), pages 15–30. Springer-Verlag.

    Google Scholar 

  11. Bryson, J. J. and Stein, L. A. (2001a). Architectures and idioms: Making progress in agent design. In Castelfranchi, C. and Lespérance, Y., editors, The Seventh International Workshop on Agent Theories, Architectures, and Languages (ATAL2000). Springer.

    Google Scholar 

  12. Bryson, J. J. and Stein, L. A. (2001b). Modularity and design in reactive intelligence. In Proceedings of the 17th International Joint Conference on Artificial Intelligence, pages 1115–1120, Seattle. Morgan Kaufmann.

    Google Scholar 

  13. Chapman, D. (1987). Planning for conjunctive goals. Artificial Intelligence, 32:333–378.

    Article  MATH  MathSciNet  Google Scholar 

  14. Chomsky, N. (1980). Rules and representations. Brain and Behavioral Sciences, 3:1–61.

    Article  Google Scholar 

  15. Dean, T. and Boddy, M. (1988). An analysis of time-dependent planning. In Proceedings of the Seventh National Conference on Artificial Intelligence (AAAI-88), pages 49–54, Saint Paul, Minnesota, USA. AAAI Press/MIT Press.

    Google Scholar 

  16. Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977). Maximumlikelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society series B, 39:1–38.

    MATH  MathSciNet  Google Scholar 

  17. Firby, J. (1987). An investigation into reactive planning in complex domains. In Proceedings of the National Conference on Artificial Intelligence (AAAI), pages 202–207.

    Google Scholar 

  18. Fodor, J. A. (1983). The Modularity of Mind. Bradford Books. MIT Press, Cambridge, MA.

    Google Scholar 

  19. Gat, E. (1991). Reliable Goal-Directed Reactive Control of Autonomous Mobile Robots. PhD thesis, Virginia Polytechnic Institute and State University.

    Google Scholar 

  20. Gat, E. (1998). Three-layer architectures. In Kortenkamp, D., Bonasso, R. P., and Murphy, R., editors, Artificial Intelligence and Mobile Robots: Case Studies of Successful Robot Systems, pages 195–210. MIT Press, Cambridge, MA.

    Google Scholar 

  21. Georgeff, M. P. and Lansky, A. L. (1987). Reactive reasoning and planning. In Proceedings of the Sixth National Conference on Artificial Intelligence (AAAI-87), pages 677–682, Seattle, WA.

    Google Scholar 

  22. Hartmann, G. and Wehner, R. (1995). The ant’s path integration system:Aneural architecture. Bilogical Cybernetics, 73:483–497.

    MATH  Google Scholar 

  23. Hexmoor, H., Horswill, I., and Kortenkamp, D. (1997). Special issue: Software architectures for hardware agents. Journal of Experimental & Theoretical Artificial Intelligence, 9(2/3).

    Google Scholar 

  24. Humphrys, M. (1997). Action Selection methods using Reinforcement Learning. PhD thesis, University of Cambridge.

    Google Scholar 

  25. Konolige, K. and Myers, K. (1998). The Saphira architecture for autonomous mobile robots. In Kortenkamp, D., Bonasso, R. P., and Murphy, R., editors, Artificial Intelligence and Mobile Robots: Case Studies of Successful Robot Systems, chapter 9, pages 211–242. MIT Press, Cambridge, MA.

    Google Scholar 

  26. Kortenkamp, D., Bonasso, R. P., and Murphy, R., editors (1998). Artificial Intelligence and Mobile Robots: Case Studies of Successful Robot Systems. MIT Press, Cambridge, MA.

    Google Scholar 

  27. Larman, C. (2001). Applying UML and Patterns: An Introduction to Object-Oriented Ana-lysis and Design and the Unified Process. Prentice Hall, 2 nd edition.

    Google Scholar 

  28. Maes, P. (1990). Situated agents can have goals. In Maes, P., editor, Designing Autonomous Agents: Theory and Practice from Biology to Engineering and back, pages 49–70. MIT Press, Cambridge, MA.

    Google Scholar 

  29. Malcolm, C. and Smithers, T. (1990). Symbol grounding via a hybrid architecture in an autonomous assembly system. In Maes, P., editor, Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back, pages 123–144. MIT Press, Cambridge, MA.

    Google Scholar 

  30. Minsky, M. (1985). The Society of Mind. Simon and Schuster Inc., NewYork, NY.

    Google Scholar 

  31. Parnas, D. L. and Clements, P. C. (1986). A rational design process: How and why to fake it. IEEE Transactions on Software Engineering, SE-12(2):251–7.

    Google Scholar 

  32. Parnas, D. L., Clements, P. C., and Weiss, D. M. (1985). The modular structure of complex systems. IEEE Transactions on Software Engineering, SE-11(3):259–266.

    Article  Google Scholar 

  33. Pauls, J. (2001). Pigs and people. in preperation.

    Google Scholar 

  34. Perkins, S. (1998). Incremental Acquisition of Complex Visual Behaviour using Genetic Programming and Shaping. PhD thesis, University of Edinburgh. Department of Artificial Intelligence.

    Google Scholar 

  35. Sengers, P. (1998). Do the thing right: An architecture for action expression. In Sycara, K. P. and Wooldridge, M., editors, Proceedings of the Second International Conference on Autonomous Agents, pages 24–31. ACM Press.

    Google Scholar 

  36. Sierra, C., de Màntaras, R. L., and Busquets, D. (2001). Multiagent bidding mechanisms for robot qualitative navigation. In Castelfranchi, C. and Lespérance, Y., editors, The Se-venthInternational Workshop on Agent Theories, Architectures, and Languages (ATAL2000). Springer.

    Google Scholar 

  37. Tyrrell, T. (1993). Computational Mechanisms for Action Selection. PhD thesis, University of Edinburgh. Centre for Cognitive Science.

    Google Scholar 

  38. van Breemen, A. (2002). Integrating agents in software applications. In this volume.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bryson, J.J. (2003). The Behavior-Oriented Design of Modular Agent Intelligence. In: Carbonell, J.G., Siekmann, J., Kowalczyk, R., Müller, J.P., Tianfield, H., Unland, R. (eds) Agent Technologies, Infrastructures, Tools, and Applications for E-Services. NODe 2002. Lecture Notes in Computer Science(), vol 2592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36559-1_7

Download citation

  • DOI: https://doi.org/10.1007/3-540-36559-1_7

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00742-5

  • Online ISBN: 978-3-540-36559-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics