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ABSTRACT

In this paper, we evaluate the stability of a plan solution at the task level and argue that it is important for task structure based multi-agent replanning. With a plan solution represented by a TÆMS (Task Analysis, Environment Modeling and Simulation) task structure, we define new metrics of the stability of a TÆMS solution and use it to rank and recommend plan candidates. We preliminarily evaluate our approach with a producer-consumer-transporter domain.

REFERENCES

• 1: Thomas Bartold , Edmund Durfee, Limiting disruption in multiagent replanning, Proceedings of the second international joint conference on Autonomous agents and multiagent systems, July 14-18, 2003, Melbourne, Australia [doi>10.1145/860575.860584]
• 2: M. Fox, A. Gerevini, D. Long, and I. Serina. Plan stability: Replanning versus plan repair. In Proc. Of the 16th Int. Conf. on Automate Planning and Scheduling (ICAPS-06), 2006.
• 3: Bryan Horling , Brett Benyo , Victor Lesser, Using self-diagnosis to adapt organizational structures, Proceedings of the fifth international conference on Autonomous agents, p.529-536, May 2001, Montreal, Quebec, Canada [doi>10.1145/375735.376436]
• 4: V. Lesser , K. Decker , T. Wagner , N. Carver , A. Garvey , B. Horling , D. Neiman , R. Podorozhny , M. Nagendra Prasad , A. Raja , R. Vincent , P. Xuan , X. Q. Zhang, Evolution of the GPGP/TÆMS Domain-Independent Coordination Framework, Autonomous Agents and Multi-Agent Systems, v.9 n.1-2, p.87-143, July-September 2004 [doi>10.1023/B:AGNT.0000019690.28073.04]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence

General Terms:
Algorithms

Keywords:
adaptation, multi-agent planning