Principled Monitoring of Distributed Agents for Detection of Coordination Failure

There is a very rich variety of systems of autonomous agents, be it software or robotic agents. In particular, multi-agent systems can include agents that may be part of a team and need to coordinate their actions during their distributed task execution. This coordination requires an agent to observe, i.e., to monitor, the other agents in order to detect a possible coordination failure of the team. Several researchers have addressed the problem of monitoring for single or multiple agent systems and have contributed successful, but mainly application-specific, approaches. In this paper, we aim at contributing a unifying, domain-independent statement of the distributed multi-agent monitoring problem. We define the problem in terms of a pre-defined desirable joint state and an observation-state mapping. Given a concrete joint observation during execution, we show how an agent can detect a possible coordination failure by processing the observation-state mapping and the desirable joint state. To illustrate the generality of our formalism, one of the main contributions of the paper, we represent several previously studied examples within our formalism. We note that basic failure detection algorithms can be computationally expensive. We further contribute an efficient method for failure detection that builds upon an off-line compilation of the principled relations introduced. We show empirical results that demonstrate this effectiveness.

[1]  Lynne E. Parker,et al.  ALLIANCE: an architecture for fault tolerant multirobot cooperation , 1998, IEEE Trans. Robotics Autom..

[2]  Maja J. Mataric,et al.  Interaction and intelligent behavior , 1994 .

[3]  Hiroaki Kitano,et al.  The RoboCup Synthetic Agent Challenge 97 , 1997, IJCAI.

[4]  Masaru Ishii,et al.  Cooperation by observation: the framework and basic task patterns , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[5]  Milind Tambe,et al.  Tracking Dynamic Team Activity , 1996, AAAI/IAAI, Vol. 1.

[6]  Richard Washington,et al.  Markov tracking for agent coordination , 1998, AGENTS '98.

[7]  Milind Tambe,et al.  Towards Flexible Teamwork , 1997, J. Artif. Intell. Res..

[8]  Milind Tambe,et al.  Intelligent Agents for Interactive Simulation Environments , 1995, AI Mag..

[9]  R. Arkin,et al.  Behavioral diversity in learning robot teams , 1998 .

[10]  Marcus J. Huber,et al.  Multiple roles, multiple teams, dynamic environment: autonomous Netrek agents , 1997, AGENTS '97.

[11]  Milind Tambe,et al.  Robust Agent Teams via Socially-Attentive Monitoring , 2000, J. Artif. Intell. Res..