TAEMS: A Framework for Task Analysis, Environment Modeling, and Simulation
Summary: Formal approaches to specifying how the mental state of an agent entails that it perform particular actions put the agent at the center of analysis. For some questions and purposes, it is more realistic and convenient for the center of analysis to be the task environment, domain, or society of which agents will be a part. We are constructing such a task environment-oriented modeling framework that can work hand in hand with more agent-centered approaches. In our approach, careful attention is paid to the quantitative computational interrelationships between tasks, to what information is available (and when) to update an agent's mental state, and to the general structure of the task environment rather than single-instance examples. A task environment model can be used for both analysis and simulation; it avoids the methodological problems of relying solely on single-instance examples, and provides concrete, meaningful characterizations with which to state general theories.
To date we have constructed models in the context of cooperative distributed problem solving and real-time scheduling. We are now working on computational models of organizations such as hospitals, managing software engineering projects, and distributed / multi-agent information retrieval.
Horling, Bryan; Lesser, Victor; Vincent, Regis and Wagner, Thomas. The Soft Real-Time Agent Control Architecture. Autonomous Agents and Multi-Agent Systems, Volume 12, Number 1, Springer Science+Business Media , pp. 35-92. 2006. An earlier version is available as UMass Computer Science Technical Report 2002-14.
Lesser, V.; Decker, K.; Wagner, T.; Carver, N.; Garvey, A.; Horling, B.; Neiman, D.; Podorozhny, R.; NagendraPrasad, M.; Raja, A.; Vincent, R.; Xuan, P.; Zhang, X.Q. Evolution of the GPGP/TAEMS Domain-Independent Coordination Framework. Autonomous Agents and Multi-Agent Systems, Volume 9, Number 1, Kluwer Academic Publishers, pp. 87-143. 2004. This is a revised version of the paper that appeared in Proceedings 1st International Conference on Autonomous Agents and Multi-Agent Systems, 2002.
Becker, Raphen; Lesser, Victor; Zilberstein, Shlomo. Decentralized Markov Decision Processes with Event-Driven Interactions. The Third International Joint Conference on Autonomous Agents and Multi Agent Systems, Volume 1, IEEE Computer Society, pp. 302-309. 2004.
Wagner, Tom; Horling, Bryan; Lesser, Victor; Phelps, John; and Guralnik, Valerie. The Struggle for Reuse: Pros and Cons of Generalization in Taems and its Impact on Technology Transition. Proceedings of the ISCA 12th International Conference on Intelligent and Adaptive Systems and Software Engineering (IASSE-2003). 2003.
Horling, Bryan; Mailler, Roger; Shen, Jiaying; Vincent, Regis, and Lesser, Victor. Using Autonomy, Organizational Design and Negotiation in a Distributed Sensor Network. Distributed Sensor Networks: A multiagent perspective, Lesser, Victor; Ortiz, Charles; and Tambe, Milind, ed., Kluwer Academic Publishers, pp. 139-183. 2003. Book chapter.
Horling, Bryan; Lesser, Victor; Vincent, Regis and Wagner, Thomas. The Soft Real-Time Agent Control Architecture. Proceedings of the AAAI/KDD/UAI-2002 Joint Workshop on Real-Time Decision Support and Diagnosis Systems. 2002. Also available as UMass Computer Science Tech Report 02-14.
Horling, Bryan; Lesser, Victor; Vincent, Regis; and Wagner, Tom. The Soft Real-Time Agent Control Architecture. UMass Computer Science Technical Report 2002-14, Number 02-14, University of Massachusetts. 2002. See also this paper.
Lesser, V.; Decker, K.; Wagner, T.; Carver, N.; Garvey, A.; Horling, B.; Neiman, D.; Podorozhny, R.; NagendraPrasad, M.; Raja, A.; Vincent, R.; Xuan, P.; Zhang, X.Q. Evolution of the GPGP/TAEMS Domain-Independent Coordination Framework. Proceedings 1st International Conference on Autonomous Agents and Multi-Agent Systems (Plenary Lecture/Extended Abstract), pp. 1-2. 2002. The full version is available as University of Massachusetts/Amherst Computer Science Technical Report 02-03.
Horling, Bryan, Vincent, Regis, Mailler, Roger, Shen, Jiaying, Becker, Raphen, Rawlins, Kyle and Lesser, Victor. Distributed Sensor Network for Real Time Tracking. Proceedings of the 5th International Conference on Autonomous Agents, ACM Press, pp. 417-424. 2001.
Wagner, Thomas, and Horling, Bryan. The Struggle for Reuse and Domain Independence: Research with TAEMS, DTC and JAF. Proceedings of the 2nd Workshop on Infrastructure for Agents, MAS, and Scalable MAS (Agents 2001), AAAI. 2001.
Vincent, Regis; Horling, Bryan; and Lesser, Victor. An Agent Infrastructure to Build and Evaluate Multi-Agent Systems: The Java Agent Framework and Multi-Agent System Simulator. Lecture Notes in Artificial Intelligence: Infrastructure for Agents, Multi-Agent Systems, and Scalable Multi-Agent Systems, Volume 1887, Wagner and Rana (eds.), Springer,, pp. 102-127. 2001.
Vincent, Regis, Horling, Bryan, Lesser, Victor. Experiences in Simulating Multi-Agent Systems Using TAEMS. The Fourth International Conference on MultiAgent Systems (ICMAS 2000), AAAI. 2000.
Paul, Utgoff, David, Jensen,Victor, Lesser. Inferring Task Structure From Data. International Conference on Machine Learning. 2000.
Horling, Bryan, Benyo, Brett, and Lesser, Victor. Using Self-Diagnosis to Adapt Organizational Structures. Computer Science Technical Report 1999-64, Number 1999-64, University of Massachusetts. 1999.
Jensen, David; Atighetchi, Michael; Vincent, Régis; and Lesser, Victor. Learning Quantitative Knowledge for Multiagent Coordination. 16th National Conference on Artificial Intelligence (AAAI-99), American Association for Artificial Intelligence, pp. 24-31. 1999.
Horling, Bryan; Lesser, Victor; Vincent, Regis; Wagner, Tom; Raja, Anita; Zhang, Shelley; Decker, Keith; and Garvey, Alan. The TAEMS White Paper. 1999.
Wagner, Thomas A., Garvey, Alan J. and Lesser, Victor R.. Criteria Directed Task Scheduling. Journal for Approximate Reasoning (Special Issue on Scheduling), Volume 19, Elsevier Science Inc., pp. 91-118. 1998. A version is also available as UMass Computer Science Technical Report 1997-59.
Decker, Keith. Task Environment Centered Simulation. Simulating Organizations: Computational Models of Institutions and Groups, AAAI Press/MIT Press. 1996.
Decker, Keith. TAEMS: A Framework for Environment Centered Analysis & Design of Coordination Mechanisms. Foundations of Distributed Artificial Intelligence, Chapter 16, G. O Hare and N. Jennings (eds.), Wiley Inter-Science, pp. 429-448. 1996.
Nagendra, Prasad, M.V., Decker, K., Garvey, A., Lesser, V.. Exploring Organizational Designs with TAEMS: A case study of distributed data processing. Proceedings of the Second International Conference on Multi-Agent Systems, AAAI Press, pp. 283-290. 1996.
Decker, K.. Environment Centered Analysis and Design of Coordination Mechanisms. Ph.D. Thesis, Department of Computer Science, University of Massachusetts, Amherst. 1995.
Decker, Keith, and Lesser, Victor. Task Environment Centered Design of Organizations. AAAI Spring Symposium on Computational Organization Design. 1994.
Decker, K., and Lesser, V.. An Approach to Analyzing the Need for Meta-Level Communication. International Joint Conference on Artificial Intelligence, Volume 1. 1993.
Decker K., and Lesser, V.R.. Quantitative Modeling of Complex Computational Task Environments. Proceedings of the Eleventh National Conference on Artificial Intelligence. 1993.
Decker, K., Lesser, V.. A One-Shot Dynamic Coordination Algorithm for Distributed Sensor Networks.. Proceeding of the Eleventh National Conference on Artificial Intelligence, AAAI, pp. 210-216. 1993.
Decker, K.; Lesser, V. R.. Quantitative Modeling of Complex Environments.. International Journal of Intelligent Systems in Accounting, Finance and Management. Special Issue on Mathematical and Computational Models and Characteristics of Agent Behaviour., Volume 2, John Wiley & Sons, Ltd., pp. 215-234. 1993.