Brahms An Agent-Oriented Language for Work Practice Simulation and Multi-Agent Systems Development

  • Maarten Sierhuis
  • William J. Clancey
  • Ron J.J. van Hoof


Brahms is a multi-agent modeling language for simulating human work practice that emerges from work processes in organizations. The same Brahms language can be used to implement and execute distributed multi-agent systems, based on models of work practice that were first simulated. Brahms demonstrates how a multi-agent belief-desire-intention language, symbolic cognitive modeling, traditional business process modeling, activity-and situated cognition theories are brought together in a coherent approach for analysis and design of organizations and human-centered systems.


International Space Station Composite Activity Primitive Activity Mission Operation Java Object 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



Brahms development started in 1992 as a collaboration between the former R&D center of the then NYNEX corporation (NYNEX Science and Technology) and the former Institute for Research on Learning (IRL), a spin off of Xerox PARC. Since 1998, Brahms has been developed and used by the Work Systems Design and Evaluation group in NASA Ames’ Intelligent Systems division. We thank all our NYNEX, IRL and NASA funders over the past sixteen years. In particular, we like to thank Jim Euchner (NYNEX) and Mike Shafto (NASA) for their continued support of Brahms and our Brahms research team.


  1. 1.
    Acquisti, A., Sierhuis, M., Clancey, W.J., Bradshaw, J.M.: Agent based modeling of collaboration and work practices onboard the international space station. In: 11th Computer-Generated Forces and Behavior Representation Conference, pp. p.181–188. Orlando, Fl. (2002)Google Scholar
  2. 2.
    Bordini, R.H., H§bner, J.F., Wooldridge, M.: Programming multi-agent systems in Agent Speak using Jason. Series in Agent Technology. Wiley (2007)CrossRefMATHGoogle Scholar
  3. 3.
    Brownston, L., Farrell, R., Kant, E., Martin, N.: Programming Expert Systems in OPS5. Addison-Wesley (1985)Google Scholar
  4. 4.
    Bruinsma, G., de Hoog, R.: Exploring protocols for multidisciplinary disaster response using adaptive workflow simulation. In: B.V.d. Walle, M. M. Turoff (eds.) International Conference on Information System for Crisis Response and Management (ISCRAM). Newark, New Jersey (2006)Google Scholar
  5. 5.
    Clancey, W.: Heuristic classification. Artificial Intelligence 27(3), 289–350 (1985)CrossRefGoogle Scholar
  6. 6.
    Clancey, W., Sachs, P., Sierhuis, M., Hoof, R.v.: Brahms: Simulating practice for work systems design. International Journal on Human-Computer Studies 49, 831–865 (1998)CrossRefGoogle Scholar
  7. 7.
    Clancey, W., Sierhuis, M., Alena, R., Berrios, D., Dowding, J., Graham, J., Tyree, K., Hirsh, R., Garry, W., Semple, A., Buckingham Shum, S., Shadbolt, N., Rupert, S.: Automating capcom using mobile agents and robotic assistants (2007)Google Scholar
  8. 8.
    Clancey, W.J.: Simulating activities: Relating motives, deliberation, and attentive coordination. Cognitive Systems Research 3(3), 471–499 (2002)CrossRefGoogle Scholar
  9. 9.
    Clancey, W.J., Sierhuis, M., Seah, C., Reynolds, F., Hall, T., Scott, M.: Multi-agent simulation to implementation: A practical engineering methodology for designing space flight operations. In: A. Artikis, G. O’Hare, K. Stathis, G. Vouros (eds.) The Eighth Annual International Workshop "Engineering Societies in the Agents World"(ESAW07), vol. LNAI. Springer, London (2008)Google Scholar
  10. 10.
    Fisher, M., Pearce, E., Wooldridge, M., Sierhuis, M., Visser, W., Bordini, R.H.: Towards the verifications of human-robot teams. In: IEEE ISoLA Workshop on Leveraging Applications of Formal Methods, Verification, and Validation.Loyola College Graduate Center, Columbia, MD (2005)Google Scholar
  11. 11.
    Forgy, C.: Rete: A fast algorithm for the many pattern/many object pattern match problem. Artificial Intelligence 19, 17–37 (1982)CrossRefGoogle Scholar
  12. 12.
    Hirsh, R., Graham, J., Tyree, K., Sierhuis, M., Clancey, W.J.: Intelligence for human-robotic planetary surface robots. In: A.M. Howard, E.W. Tunstel (eds.) Intelligence for Space Robotics. TSI Press, Albuquerque (2006)Google Scholar
  13. 13.
    Konolige, K.: A Deduction Model of Belief. Morgan Kaufmann, San Mateo, CA (1986)MATHGoogle Scholar
  14. 14.
    Leont’ev, A.N.: Activity, Consciousness and Personality. Prentice-Hall, Englewood Cliffs, NJ (1978)Google Scholar
  15. 15.
    Netten, N., Bruinsma, G., van Someren, M., de Hoog, R.: Task-adaptive information distribution for synamic collaborative emergency response. International Journal of Intelligent Control and Systems 11(4), 238–247 (2007)Google Scholar
  16. 16.
    vanPutten, B.J., Dignum, V., Sierhuis, M., Wolfe, S.R.: Opera and brahms: a symphony? In: Agent-Oriented Software Engineering (AOSE)2008 at The Sixth International Joint Conference on Autonomous Agents & Multi-Agent Systems (AAMAS 2008), vol. Forthcoming LNCS Proceedings. Springer, Estoril, Portugal (2008)Google Scholar
  17. 17.
    Seah, C., Sierhuis, M., Clancey, W.: Multi-agent modeling and simulation approach for design and analysis of mer mission operations. In: 2005 International Conference on Human-Computer Interface Advances for Modeling and Simulation (SIMCHI’05). 2005 Western Simulation Multiconference (WMC’05), New Orleans, Louisiana (2005)Google Scholar
  18. 18.
    Sierhuis, M.: Modeling and simulating work practice; brahms: A multiagent modeling and simulation language for work system analysis and design. Ph.d. thesis, University of Amsterdam, SIKS Dissertation Series No. 2001-10 (2001)Google Scholar
  19. 19.
    Sierhuis, M.: ”it’s not just goals all the way down”– ”it’s activities all the way down”. In: G.M.P. O’Hare, A. Ricci, M.J. O’Grady, O. Dikenelli (eds.) Engineering Societies in the Agents World VII, 7th International, Workshop, ESAW2006, Dublin, Ireland, September 6-8, 2006, Revised Selected and Invited Papers, Lecture Notes in Computer Science, vol. LNCS 4457/2007, pp. 1–24. Springer, Dublin, Ireland (2007)Google Scholar
  20. 20.
    Sierhuis, M., Acquisti, A., Clancey, W.: Multiagent plan execution and work practice: Modeling plans and practices onboard the iss. In: 3rd International NASA Workshop on Planning and Scheduling for Space. Houston, TX (2002)Google Scholar
  21. 21.
    Sierhuis, M., Clancey, W., Seah, C., Trimble, J., Sims, M.H.: Modeling and simulation for mission operations work system design. Journal of Management Information Systems Vol. 19(No. 4), 85–129 (2003)CrossRefGoogle Scholar
  22. 22.
    Sierhuis, M., Clancey, W.J., Seah, C.H.: Organization and work systems design and engineering; from simulation to implementation of multi-agent systems. In: Agent Directed Simulation, chap. 13. Wiley(To Appear)Google Scholar
  23. 23.
    Sierhuis, M., Diegelman, T.E., Seah, C., Shalin, V., Clancey, W.J., Selvin, A.M.: Agent-based simulation of shuttle mission operations. In: Agent-Directed Simulation 2007 part of the 2007 Spring Simulation Multiconference, pp. 53–60.The Society for Modeling and Simulation International, ACM/SIGSIM, Norfolk, VA (2007)Google Scholar
  24. 24.
    Sierhuis, M., Sims, M., Clancey, W., Lee, P.: Applying multiagent simulation to planetary surface operations. In: L. Chaudron (ed.) COOP’2000 workshop on Modelling Human Activity, pp. 19–28. Sophia Antipolis, France (2000)Google Scholar
  25. 25.
    Suchman, L.: Representations of work. Communications of the ACM/Special Issue 38(9) (1995)Google Scholar
  26. 26.
    Suchman, L.A.: Plans and Situated Action: The Problem of Human Machine Communication. Cambridge University Press, Cambridge, MA (1987)Google Scholar
  27. 27.
    Vygotsky, L.S.: Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge, MA (1978)Google Scholar
  28. 28.
    Wolfe, S.R., Jarvis, P.A., Enomoto, F.Y., Sierhuis, M.: Comparing route selection strategies in collaborative traffic flow management. In: Intelligent Agent Technology (IAT 2007). IEEE press, Fremont, CA,USA (2007)Google Scholar
  29. 29.
    Wolfe, S.R., Sierhuis, M., Jarvis, P.A.: To bdi, or not to bdi: Design choices in an agent based traffic flow management simulation. In: Agent Directed Simulation 2008 held at the SpringSim Multi-Conference 2008. ACM, Ottawa, Canada (2008)Google Scholar

Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  • Maarten Sierhuis
    • 1
    • 2
  • William J. Clancey
    • 3
  • Ron J.J. van Hoof
    • 4
  1. 1.NASA Ames Research CenterCarnegie Mellon University Silicon ValleyMoffett Field
  2. 2.Man-Machine Interaction GroupDelft University of TechnologyMekelweg 4The Netherlands
  3. 3.NASA Ames Research CenterMoffett Field
  4. 4.PerotSystems/NASA Ames Research CenterMoffett Field

Personalised recommendations