Crowding games are sequentially solvable
International Journal of Game Theory
The Byzantine Generals Problem
ACM Transactions on Programming Languages and Systems (TOPLAS)
Algorithms, games, and the internet
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Journal of the ACM (JACM)
Tight bounds for worst-case equilibria
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
The Structure and Complexity of Nash Equilibria for a Selfish Routing Game
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Near-optimal network design with selfish agents
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Proceedings of the twenty-second annual symposium on Principles of distributed computing
Rational secret sharing and multiparty computation: extended abstract
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
The Price of Stability for Network Design with Fair Cost Allocation
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
On nash equilibria for a network creation game
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
The communication complexity of coalition formation among autonomous agents
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Performance Guarantees of Local Search for Multiprocessor Scheduling
INFORMS Journal on Computing
Strong equilibrium in cost sharing connection games
Proceedings of the 8th ACM conference on Electronic commerce
Network formation games with local coalitions
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
On the Value of Coordination in Network Design
SIAM Journal on Computing
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
Strong and correlated strong equilibria in monotone congestion games
WINE'06 Proceedings of the Second international conference on Internet and Network Economics
On the price of anarchy and stability of correlated equilibria of linear congestion games,,
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Strong price of anarchy for machine load balancing
ICALP'07 Proceedings of the 34th international conference on Automata, Languages and Programming
Approximate Strong Equilibrium in Job Scheduling Games
SAGT '08 Proceedings of the 1st International Symposium on Algorithmic Game Theory
On the quality and complexity of pareto equilibria in the job scheduling game
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Game theoretical applications for multi-agent systems
Expert Systems with Applications: An International Journal
Conflicting Congestion Effects in Resource Allocation Games
Operations Research
On the verification and computation of strong nash equilibrium
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Approximate strong equilibria in job scheduling games with two uniformly related machines
Discrete Applied Mathematics
Hi-index | 0.00 |
A Nash Equilibrium (NE) is a strategy profile resilient to unilateral deviations, and is predominantly used in the analysis of multiagent systems. A downside of NE is that it is not necessarily stable against deviations by coalitions. Yet, as we show in this paper, in some cases, NE does exhibit stability against coalitional deviations, in that the benefits from a joint deviation are bounded. In this sense, NE approximates strong equilibrium. Coalition formation is a key issue in multiagent systems. We provide a framework for quantifying the stability and the performance of various assignment policies and solution concepts in the face of coalitional deviations. Within this framework we evaluate a given configuration according to three measures: (i) IRmin: the maximal number α, such that there exists a coalition in which the minimal improvement ratio among the coalition members is α, (ii) IRmax: the maximal number α, such that there exists a coalition in which the maximal improvement ratio among the coalition members is α, and (iii) DRmax: the maximal possible damage ratio of an agent outside the coalition. We analyze these measures in job scheduling games on identical machines. In particular, we provide upper and lower bounds for the above three measures for both NE and the well-known assignment rule Longest Processing Time (LPT). Our results indicate that LPT performs better than a general NE. However, LPT is not the best possible approximation. In particular, we present a polynomial time approximation scheme (PTAS) for the makespan minimization problem which provides a schedule with IRmin of 1 + Ɛ for any given Ɛ. With respect to computational complexity, we show that given an NE on m ≤ 3 identical machines or m ≤ 2 unrelated machines, it is NP-hard to determine whether a given coalition can deviate such that every member decreases its cost.