1 / 12

Modeling the Iterated Prisoners' Dilemma for Strategic Decision-Making

Explore a model analyzing the dilemmas of repeated prisoner interactions. Understand inputs, strategies, and future choices to maximize profit. Utilize Python software for simulation and strategic decision-making. Discover how cooperation can still arise even in unfavorable scenarios.

qabil
Download Presentation

Modeling the Iterated Prisoners' Dilemma for Strategic Decision-Making

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Un modelo sobre el dilema del prisionero iterado (A model about the iterated prisoners' dilemma) Victoria Gradín Alfonso Pérez Más vale bueno por conocer(Better good later)

  2. A. Rapoport – M. Chammah

  3. Model overview • Inputs • Payments matrix • History • Parameters • History Memory Opponent + Payments Future Choice • Outputs • Strategies

  4. Constrains • Choice Future Opponent+Payments Memory • Choice: Maximum profit • Future: Decision tree • Opponent: Statistical distributions • Memory: Counters

  5. Memory • Count: Add 1 • sum(n) = • sum(n+1) =

  6. Opponent • Beta distribution: • Beta(1,1) = Uniform • Dispersion gets lower as information grows • In the long run, Beta's mean value approaches the frequency

  7. Future • Bifurcations • Tree of possible futures

  8. Choice • Calculate cooperation profits, and defection profits • Chose the option that maximizes profits

  9. Current state • Software: Python implementation • Verification of some reasonable properties (adaptive, non-exploitable) against fixed strategies (alld, allc, cooperative-tft) • Parameter estimation for one kind of behavior

  10. Cooperation in matrix V • Why cooperate in the less favorable case?

  11. Future tree detail

  12. Preliminary conclusions • Sometimes, it's better good to know • Cooperation is possible, even under adverse circumstances, with selfish behaviour (no need for altruism).

More Related