TY - GEN
T1 - Coalition structure generation in multi-agent systems with positive and negative externalities
AU - Rahwan, Talal
AU - Michalak, Tomasz
AU - Jennings, Nicholas R.
AU - Wooldridge, Michael
AU - McBurney, Peter
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - Coalition structure generation has received considerable attention in recent research. Several algorithms have been proposed to solve this problem in Characteristic Function Games (CFGs), where every coalition is assumed to perform equally well in any coalition structure containing it. In contrast, very little attention has been given to the more general Partition Function Games (PFGs), where a coalition's effectiveness may change from one coalition structure to another. In this paper, we deal with PFGs with positive and negative externalities. In this context, we identify the minimum search that is required in order to establish a bound on the quality of the best coalition structure found. We then develop an anytime algorithm that improves this bound with further search, and show that it outperforms the existing state-of-the-art algorithms by orders of magnitude.
AB - Coalition structure generation has received considerable attention in recent research. Several algorithms have been proposed to solve this problem in Characteristic Function Games (CFGs), where every coalition is assumed to perform equally well in any coalition structure containing it. In contrast, very little attention has been given to the more general Partition Function Games (PFGs), where a coalition's effectiveness may change from one coalition structure to another. In this paper, we deal with PFGs with positive and negative externalities. In this context, we identify the minimum search that is required in order to establish a bound on the quality of the best coalition structure found. We then develop an anytime algorithm that improves this bound with further search, and show that it outperforms the existing state-of-the-art algorithms by orders of magnitude.
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M3 - Conference contribution
AN - SCOPUS:78149236028
SN - 9781577354260
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 257
EP - 263
BT - IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence
PB - International Joint Conferences on Artificial Intelligence
T2 - 21st International Joint Conference on Artificial Intelligence, IJCAI 2009
Y2 - 11 July 2009 through 16 July 2009
ER -