Achieving pareto optimality through distributed learning
We propose a simple payoff-based learning rule that is completely decentralized, and that leads to an efficient configuaration of actions in any n-person finite strategic-form game with generic payoffs. The algorithm follows the theme of exploration versus exploitation and is hence stochastic in na...
Main Authors: | Young, H, Marden, J, Pao, L |
---|---|
Format: | Working paper |
Published: |
University of Oxford
2011
|
Similar Items
-
Achieving Pareto Optimality Through Distributed Learning.
by: Young, H, et al.
Published: (2011) -
Pareto optimality in coalition formation
by: Aziz, H, et al.
Published: (2013) -
Pareto-optimal phylogenetic tree reconciliation
by: Libeskind-Hadas, Ran, et al.
Published: (2015) -
Price of pareto optimality in hedonic games
by: Elkind, E, et al.
Published: (2016) -
Price of Pareto optimality in hedonic games
by: Elkind, E, et al.
Published: (2020)