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The Second Axelrod Tournament: A Monte Carlo Exploration of Uncertainty About the Number of Rounds in Iterated Prisoner’s Dilemma

Author

Listed:
  • Pop Gabriel

    (Babeș-Bolyai University, Romania)

  • Milencianu Mircea

    (Babeș-Bolyai University, Romania)

  • Pop Alexandra

    (Babeș-Bolyai University, Romania)

Abstract

Strategic decision-making in multi-agent interactions inside the Iterated Prisoner’s Dilemma (IPD) is investigated in this work using Monte Carlo simulations. Building on Axelrod’s work, we present a second-generation tournament with stochastic components, including unpredictable game lengths, to evaluate strategy adaptability and resilience. We analyze how uncertainty influences strategic performance by using a comparison between instances with fixed and uncertain times. We identify, using a descriptive approach, methods demonstrating important behavioral differences between deterministic and uncertain settings. The results provide understanding of adaptive learning, response dynamics, and strategic flexibility, so helping to build strong collaborative strategies for artificial intelligence and decision-making systems. Our results highlight the limitations of exclusively deterministic methods and suggest the necessity for adaptive approaches to improve long-term cooperative success.

Suggested Citation

  • Pop Gabriel & Milencianu Mircea & Pop Alexandra, 2025. "The Second Axelrod Tournament: A Monte Carlo Exploration of Uncertainty About the Number of Rounds in Iterated Prisoner’s Dilemma," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 70(1), pages 67-82.
    • Handle: RePEc:vrs:subboe:v:70:y:2025:i:1:p:67-82:n:1004
    DOI: 10.2478/subboec-2025-0004
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    References listed on IDEAS

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    1. Ben-porath, Elchanan, 1990. "The complexity of computing a best response automaton in repeated games with mixed strategies," Games and Economic Behavior, Elsevier, vol. 2(1), pages 1-12, March.
    2. John H. Nachbar, 2005. "Beliefs in Repeated Games," Econometrica, Econometric Society, vol. 73(2), pages 459-480, March.
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    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other

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