TY - GEN
T1 - Dynamic inefficiency
T2 - 4th International Symposium on Algorithmic Game Theory, SAGT 2011
AU - Berger, Noam
AU - Feldman, Michal
AU - Neiman, Ofer
AU - Rosenthal, Mishael
PY - 2011
Y1 - 2011
N2 - The price of anarchy [16] is by now a standard measure for quantifying the inefficiency introduced in games due to selfish behavior, and is defined as the ratio between the optimal outcome and the worst Nash equilibrium. However, this notion is well defined only for games that always possess a Nash equilibrium (NE). We propose the dynamic inefficiency measure, which is roughly defined as the average inefficiency in an infinite best-response dynamic. Both the price of anarchy [16] and the price of sinking [9] can be obtained as special cases of the dynamic inefficiency measure. We consider three natural best-response dynamic rules - Random Walk (RW), Round Robin (RR) and Best Improvement (BI) - which are distinguished according to the order in which players apply best-response moves. In order to make the above concrete, we use the proposed measure to study the job scheduling setting introduced in [3], and in particular the scheduling policy introduced there. While the proposed policy achieves the best possible price of anarchy with respect to a pure NE, the game induced by the proposed policy may admit no pure NE, thus the dynamic inefficiency measure reflects the worst case inefficiency better. We show that the dynamic inefficiency may be arbitrarily higher than the price of anarchy, in any of the three dynamic rules. As the dynamic inefficiency of the RW dynamic coincides with the price of sinking, this result resolves an open question raised in [3]. We further use the proposed measure to study the inefficiency of the Hotelling game and the facility location game. We find that using different dynamic rules may yield diverse inefficiency outcomes; moreover, it seems that no single dynamic rule is superior to another.
AB - The price of anarchy [16] is by now a standard measure for quantifying the inefficiency introduced in games due to selfish behavior, and is defined as the ratio between the optimal outcome and the worst Nash equilibrium. However, this notion is well defined only for games that always possess a Nash equilibrium (NE). We propose the dynamic inefficiency measure, which is roughly defined as the average inefficiency in an infinite best-response dynamic. Both the price of anarchy [16] and the price of sinking [9] can be obtained as special cases of the dynamic inefficiency measure. We consider three natural best-response dynamic rules - Random Walk (RW), Round Robin (RR) and Best Improvement (BI) - which are distinguished according to the order in which players apply best-response moves. In order to make the above concrete, we use the proposed measure to study the job scheduling setting introduced in [3], and in particular the scheduling policy introduced there. While the proposed policy achieves the best possible price of anarchy with respect to a pure NE, the game induced by the proposed policy may admit no pure NE, thus the dynamic inefficiency measure reflects the worst case inefficiency better. We show that the dynamic inefficiency may be arbitrarily higher than the price of anarchy, in any of the three dynamic rules. As the dynamic inefficiency of the RW dynamic coincides with the price of sinking, this result resolves an open question raised in [3]. We further use the proposed measure to study the inefficiency of the Hotelling game and the facility location game. We find that using different dynamic rules may yield diverse inefficiency outcomes; moreover, it seems that no single dynamic rule is superior to another.
UR - http://www.scopus.com/inward/record.url?scp=80054044262&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-24829-0_7
DO - 10.1007/978-3-642-24829-0_7
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AN - SCOPUS:80054044262
SN - 9783642248283
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 57
EP - 68
BT - Algorithmic Game Theory - 4th International Symposium, SAGT 2011, Proceedings
Y2 - 17 October 2011 through 19 October 2011
ER -