TY - JOUR
T1 - Complexity and Approximations in Robust Coalition Formation via Max-Min k-Partitioning,
AU - Ismaili, Anisse
AU - Hazon, Noam
AU - Watanabe, Emi
AU - Yokoo, Makoto
AU - Kraus, Sarit
PY - 2019/1/1
Y1 - 2019/1/1
N2 - © 2019 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. Coalition formation is beneficial to multi-agent systems, especially when the value of a coalition depends on the relationship among its members. However, an attack can significantly damage a coalition structure by disabling agents. Therefore, getting prepared in advance for such an attack is particularly important. We study a robust k-coalition formation problem modeled by max-min k-partition of a weighted graph. We show that this problem is Σp2-complete, which holds even for k = 2 and arbitrary weights, or k = 3 and non-negative weights. We also propose the Iterated Best Response (IBR) algorithm which provides a run-time absolute bound for the approximation error and can be generalized to the max-min optimization version of any Σp2-complete problem. We tested IBR on fairly large instances of both synthetic graphs and real life networks, yielding near optimal results in a reasonable time.
AB - © 2019 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. Coalition formation is beneficial to multi-agent systems, especially when the value of a coalition depends on the relationship among its members. However, an attack can significantly damage a coalition structure by disabling agents. Therefore, getting prepared in advance for such an attack is particularly important. We study a robust k-coalition formation problem modeled by max-min k-partition of a weighted graph. We show that this problem is Σp2-complete, which holds even for k = 2 and arbitrary weights, or k = 3 and non-negative weights. We also propose the Iterated Best Response (IBR) algorithm which provides a run-time absolute bound for the approximation error and can be generalized to the max-min optimization version of any Σp2-complete problem. We tested IBR on fairly large instances of both synthetic graphs and real life networks, yielding near optimal results in a reasonable time.
UR - http://scholar.google.com/scholar?num=3&hl=en&lr=&q=allintitle%3A%20Complexity%20and%20Approximations%20in%20Robust%20Coalition%20Formation%20via%20Max-Min%20k-Partitioning%2C%20author%3AIsmaili%20OR%20author%3AHazon%20OR%20author%3AWatanabe%20OR%20author%3AYokoo%20OR%20author%3AKraus&as_ylo=2019&as_yhi=&btnG=Search&as_vis=0
M3 - مقالة
VL - 4
SP - 2036
EP - 2038
JO - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
JF - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ER -