TY - GEN
T1 - Cooperative weakest link games
AU - Bachrach, Yoram
AU - Lev, Omer
AU - Lovett, Shachar
AU - Rosenschein, Jeffrey S.
AU - Zadimoghaddam, Morteza
N1 - Publisher Copyright:
Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - We introduce Weakest Link Games (WLGs), a cooperative game modeling domains where a team's value is determined by its weakest member. The game is represented as an edge-weighted graph with designated source and target vertices, where agents are the edges. The quality of a path between the source vertex and target vertex is the minimal edge weight along the path; the value of a coalition of edges is the quality of the best path contained in the coalition, and zero if the coalition contains no such path. WLGs model joint projects where the overall achievement depends on the weakest component, such as multiple-option package deals, or transport domains where each road has a different allowable maximum load. We provide methods for computing revenue sharing solutions in WLGs, including polynomial algorithms for calculating the value of a coalition, the core, and the least-core. We also examine optimal team formation in WLGs. Though we show that finding the optimal coalition structure is NP-hard, we provide an O(log n)-approximation. Finally, we examine the agents' resistance to cooperation through the Cost of Stability.
AB - We introduce Weakest Link Games (WLGs), a cooperative game modeling domains where a team's value is determined by its weakest member. The game is represented as an edge-weighted graph with designated source and target vertices, where agents are the edges. The quality of a path between the source vertex and target vertex is the minimal edge weight along the path; the value of a coalition of edges is the quality of the best path contained in the coalition, and zero if the coalition contains no such path. WLGs model joint projects where the overall achievement depends on the weakest component, such as multiple-option package deals, or transport domains where each road has a different allowable maximum load. We provide methods for computing revenue sharing solutions in WLGs, including polynomial algorithms for calculating the value of a coalition, the core, and the least-core. We also examine optimal team formation in WLGs. Though we show that finding the optimal coalition structure is NP-hard, we provide an O(log n)-approximation. Finally, we examine the agents' resistance to cooperation through the Cost of Stability.
KW - Cooperative games
KW - Optimal coalition structure generation
KW - The core
UR - https://www.scopus.com/pages/publications/84911443807
M3 - Conference contribution
AN - SCOPUS:84911443807
T3 - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
SP - 589
EP - 596
BT - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
T2 - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Y2 - 5 May 2014 through 9 May 2014
ER -