Automated adaptation of strategic guidance in multiagent coordination

Authors:
Rajiv T. Maheswaran;Pedro Szekely;Romeo Sanchez
Affiliations:
Information Sciences Institute and Department of Computer Science, University of Southern California;Information Sciences Institute and Department of Computer Science, University of Southern California;Facultad de Ingeniería Mecánica y Eléctrica, Universidad Autónoma de Nuevo León, Mexico
Venue:
PRIMA'11 Proceedings of the 14th international conference on Agents in Principle, Agents in Practice
Year:
2011

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Abstract

We address multi-agent planning problems in dynamic environments motivated by assisting human teams in disaster emergency response. It is challenging because most goals are revealed during execution, where uncertainty in the duration and outcome of actions plays a significant role, and where unexpected events can cause large disruptions to existing plans. The key to our approach is giving human planners a rich strategy language to constrain the assignment of agents to goals and allow the system to instantiate the strategy during execution, tuning the assignment to the evolving execution state. Our approach outperformed an extensively-trained team coordinating with radios and a traditional command-center organization, and an agent-assisted team using a different approach.