Learning with Repeated-Game Strategies
Learning with Repeated-Game Strategies
We use the self-tuning Experience Weighted Attraction model with repeated-game strategies as a computer testbed to examine the relative frequency, speed of convergence and progression of a set of repeated-game strategies in four symmetric 2x2 games: Prisoner's Dilemma, Battle of the Sexes, Stag-Hunt, and Chicken. In the Prisoner's Dilemma game, we find that the strategy with the most occurrences is the "Grim-Trigger." In the Battle of the Sexes game, a cooperative pair that alternates between the two pure-strategy Nash equilibria emerges as the one with the most occurrences. In the Stag-Hunt and Chicken games, the "Win-Stay, Lose-Shift" and "Grim-Trigger" strategies are the ones with the most occurrences. Overall, the pairs that converged quickly ended up at the cooperative outcomes, whereas the ones that were extremely slow to reach convergence ended up at non-cooperative outcomes
dynamic decision-making, adaptive models, Finite Automata, Experience Weighted Attraction Model, Action Models
1-27
Ioannou, Christos A.
753c2afb-918b-4576-ba47-da42502f37c9
Romero, Julian
1f0fc2ed-1110-47e0-b98b-c40b56043251
30 July 2014
Ioannou, Christos A.
753c2afb-918b-4576-ba47-da42502f37c9
Romero, Julian
1f0fc2ed-1110-47e0-b98b-c40b56043251
Ioannou, Christos A. and Romero, Julian
(2014)
Learning with Repeated-Game Strategies.
Frontiers in Neuroscience, 8 (212), .
(doi:10.3389/fnins.2014.00212).
Abstract
We use the self-tuning Experience Weighted Attraction model with repeated-game strategies as a computer testbed to examine the relative frequency, speed of convergence and progression of a set of repeated-game strategies in four symmetric 2x2 games: Prisoner's Dilemma, Battle of the Sexes, Stag-Hunt, and Chicken. In the Prisoner's Dilemma game, we find that the strategy with the most occurrences is the "Grim-Trigger." In the Battle of the Sexes game, a cooperative pair that alternates between the two pure-strategy Nash equilibria emerges as the one with the most occurrences. In the Stag-Hunt and Chicken games, the "Win-Stay, Lose-Shift" and "Grim-Trigger" strategies are the ones with the most occurrences. Overall, the pairs that converged quickly ended up at the cooperative outcomes, whereas the ones that were extremely slow to reach convergence ended up at non-cooperative outcomes
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Published date: 30 July 2014
Keywords:
dynamic decision-making, adaptive models, Finite Automata, Experience Weighted Attraction Model, Action Models
Organisations:
Economics
Identifiers
Local EPrints ID: 366892
URI: http://eprints.soton.ac.uk/id/eprint/366892
ISSN: 1662-4548
PURE UUID: d276bcae-8b96-457f-acd8-f97de5ab8e19
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Date deposited: 14 Jul 2014 08:50
Last modified: 14 Mar 2024 17:18
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Author:
Christos A. Ioannou
Author:
Julian Romero
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