Abstract
In this paper we describe our solution to a real-time distributed tracking problem. The system works not by finding an optimal solution, but through a satisficing search for an allocation that is “goodenough” to meet the specified resource requirements, which can then be revised over time if needed. The agents in the environment are first organized by partitioning them into sectors, reducing the level of potential interaction between agents. Within each sector, agents dynamically specialize to address scanning, tracking, or other goals, which are instantiated as task structures for use by the SRTA control architecture. These elements exist to support resource allocation, which is directly effected through the use of the SPAM negotiation protocol. The agent problem solving component first discovers and generates commitments for sensors to use for gathering data, then determines if conflicts exist with that allocation, finally using arbitration and relaxation strategies to resolve such conflicts. We have empirically tested and evaluated these techniques in both the Radsim simulation environment and using the hardware-based system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bordini, R., Bazzan, A., Jannone, R., Basso, D., Vicari, R., and Lesser, V. (2002). Agentspeak(xl): Efficient intention selection in bdi agents via decision-theoretic task scheduling. In Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-2002), Bologna, Italy.
Decker, K. S. and Lesser, V. R. (1993). Quantitative modeling of complex environments. International Journal of Intelligent Systems in Accounting, Finance, and Management, 2(4):215–234. Special issue on “Mathematical and Computational Models of Organizations: Models and Characteristics of Agent Behavior”.
Horling, B. and Lesser, V. (1998). A reusable component architecture for agent construction. Master’s thesis, Department of Computer Science, University of Massachusetts, Amherst. Available as UMASS CS TR-98-30.
Horling, B., Lesser, V., Vincent, R., Raja, A., and Zhang, S. (1999). The TÆMS white paper, http://mas.cs.umass.edu/res-earch/taems/white/.
Horling, B., Lesser, V., Vincent, R., and Wagner, T. (2002). The soft real-time agent control architecture. Computer Science Technical Report TR-02-14, University of Massachusetts at Amherst.
Jensen, D., Atighetchi, M., Vincent, R., and Lesser, V. (1999). Learning quantitative knowledge for multiagent coordination. In Proceedings of the Sixteenth National Conference on Artificial Intelligence, Orlando, FL. AAAI.
Lesser, V, Horling, B., Klassner, F., Raja, A., Wagner, T., and Zhang, S. (2000). Big: An agent for resource-bounded information gathering and decision making. In Artificial Intelligence Journal, Special Issue on Internet Information Agents (also available as UMass Computer Science Technical Report 1998-52), volume 118, pages 197–244. Elsevier Science.
Mailler, R., Vincent, R., Lesser, V., Shen, J., and Middlekoop, T. (2001). Soft real-time, cooperative negotiation for distributed resource allocation. In Proceedings of the 2001 AAAI Fall Symposium on Negotiation.
Minton, S., Johnston, M. D., Philips, A. B., and Laird, P. (1992). Minimizing conflicts: A heuristic repair method for constraint satisfaction and scheduling problems. Artificial Intelligence, 58(1–3):161–205.
Raja, A. and Lesser, V. (2002). Meta-level control in multi-agent systems. Proceedings of AAAI/KDD/UAI-2002 Joint Workshop on Real-Time Decision Support and Diagnosis Systems. (Also UMass Computer Science Technical Report 01–49, Nov. 2001), WS-02-15:47–53.
Sims, M., Goldman, C., and Lesser, V. (2003). Self-organization through bottom-up coalition formation. In Proceedings of Second International Joint Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2003). To appear.
Sycara, K., Decker, K., and Williamson, M. (1997). Middle-agents for the internet. In Proceedings of IJCAI-97.
Vincent, R., Horling, B., Lesser, V., and Wagner, T. (2001). Implementing soft real-time agent control. In Proceedings of the Fifth International Conference on Autonomous Agents, pages 355–362.
Wagner, T., Garvey, A., and Lesser, V. (1998). Criteria-Directed Heuristic Task Scheduling. International Journal of Approximate Reasoning, Special Issue on Scheduling, 19(1–2):91–118. A version also available as UMASS CS TR-97-59.
Zhang, X., Raja, A., Lerner, B., Lesser, V., Osterweil, L., and Wagner, T. (2000). Integrating high-level and detailed agent coordination into a layered architecture. Lecture Notes in Computer Science: Infrastructure for Scalable Multi-Agent Systems, pages 72–79. Springer-Verlag, Berlin. Also available as UMass Computer Science Technical Report 1999-029.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Science+Business Media New York
About this chapter
Cite this chapter
Horling, B., Mailler, R., Shen, J., Vincent, R., Lesser, V. (2003). Using Autonomy, Organizational Design and Negotiation in a Distributed Sensor Network. In: Lesser, V., Ortiz, C.L., Tambe, M. (eds) Distributed Sensor Networks. Multiagent Systems, Artificial Societies, and Simulated Organizations, vol 9. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0363-7_8
Download citation
DOI: https://doi.org/10.1007/978-1-4615-0363-7_8
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5039-2
Online ISBN: 978-1-4615-0363-7
eBook Packages: Springer Book Archive