Find in Library
Search millions of books, articles, and more
Indexed Open Access Databases
Learning With Repeated-Game Strategies
oleh: Christos A. Ioannou, Julian eRomero
| Format: | Article |
|---|---|
| Diterbitkan: | Frontiers Media S.A. 2014-07-01 |
Deskripsi
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 fi□nd 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.