TY - GEN
T1 - Aspiration learning in coordination games
AU - Chasparis, Georgios C.
AU - Shamma, Jeff S.
AU - Arapostathis, Ari
PY - 2010
Y1 - 2010
N2 - We consider the problem of distributed convergence to efficient outcomes in coordination games through payoff-based learning dynamics, namely aspiration learning. The proposed learning scheme assumes that players reinforce well performed actions, by successively playing these actions, otherwise they randomize among alternative actions. Our first contribution is the characterization of the asymptotic behavior of the induced Markov chain of the iterated process by an equivalent finite-stateMarkov chain, which simplifies previously introduced analysis on aspiration learning. We then characterize explicitly the behavior of the proposed aspiration learning in a generalized version of so-called coordination games, an example of which is network formation games. In particular, we show that in coordination games the expected percentage of time that the efficient action profile is played can become arbitrarily large.
AB - We consider the problem of distributed convergence to efficient outcomes in coordination games through payoff-based learning dynamics, namely aspiration learning. The proposed learning scheme assumes that players reinforce well performed actions, by successively playing these actions, otherwise they randomize among alternative actions. Our first contribution is the characterization of the asymptotic behavior of the induced Markov chain of the iterated process by an equivalent finite-stateMarkov chain, which simplifies previously introduced analysis on aspiration learning. We then characterize explicitly the behavior of the proposed aspiration learning in a generalized version of so-called coordination games, an example of which is network formation games. In particular, we show that in coordination games the expected percentage of time that the efficient action profile is played can become arbitrarily large.
UR - http://www.scopus.com/inward/record.url?scp=79953131782&partnerID=8YFLogxK
U2 - 10.1109/CDC.2010.5717289
DO - 10.1109/CDC.2010.5717289
M3 - Conference contribution
AN - SCOPUS:79953131782
SN - 9781424477456
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 5756
EP - 5761
BT - 2010 49th IEEE Conference on Decision and Control, CDC 2010
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 49th IEEE Conference on Decision and Control, CDC 2010
Y2 - 15 December 2010 through 17 December 2010
ER -