Guided Team Selection

Gil Tidhar, Anand S. Rao, Australian Artificial Intelligence Institute, and Elizabeth A. Sonenberg, University of Melbourne, Australia

Team selection, the process of selecting a group of agents with complementary skills to achieve a goal, is an important collaborative task in multi-agent systems. Typically, team selection occurs at run-time using a first principles approach, for example after agents have exchanged relevant information about their abilities, loads, or other status. In time-critical domains such approaches may be impractical. Our work assumes that agents have limited resources and are embedded in a continuously changing world. We provide a mechanism whereby system developers can describe "recipes" for team selection in terms of the required abilities of the team, and appropriate run-time constraints. We refer to such recipes as allocations. The paper provides definitions and algorithms, and includes comparisons with related work.


This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.