Biasing the behavior of organizationally adept agents: (extended abstract)

Authors:
Daniel D. Corkill;Chongjie Zhang;Bruno Castro da Silva;Yoonheui Kim;Daniel Garant;Victor R. Lesser;Xiaoqin Zhang
Affiliations:
University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Dartmouth, North Dartmouth, MA, USA
Venue:
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Year:
2013

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Abstract

An {organizationally adept agent (OAA) adjusts its behavior when given annotated organizational guidelines. More importantly, it can also determine when such guidelines become ineffective and proactively adapt its behavior to better achieve organizational objectives. We present the high-level aspects of this architecture and analyze its effectiveness using call-center OAAs striving to extinguish fires in RoboCup Rescue scenarios.