The Unexpected Edge: Why Niceness Triumphs in Game Theory
Last Updated on December 13, 2024 by Editorial Team
Author(s): Shanaka C. DeSoysa
Originally published on Towards AI.
How βNiceβ Strategies Outperform the Rest in the Prisonerβs Dilemma
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Photo by Vasilios Muselimis on UnsplashIn the realm of strategic decision-making, an unexpected champion emerges from the game theory landscape: the βniceβ strategy. This article delves into the surprising efficacy of βniceβ strategies, specifically focusing on their dominance in the classic prisonerβs dilemma, illuminating how niceness prevails in a world of conflicts and its relevance to software engineers and data scientists.
The prisonerβs dilemma serves as a foundational concept in game theory, depicting a scenario where two rational individuals must decide whether to cooperate or defect, each aiming to maximize their own outcome. The dilemma is structured as follows:
If both players cooperate, they receive a moderate reward.If one defects while the other cooperates, the defector gets a high reward while the cooperator receives nothing.If both defect, both receive a minimal reward.
Game theory principles have broad applications, from economics to artificial intelligence. In the realm of technology, understanding strategic interactions plays a pivotal role, influencing decision-making in algorithms, machine learning, and software development.
Letβs simulate the prisonerβs dilemma using Python to explore strategies and their performances in repeated dilemmas. Hereβs a snippet of Python code showcasing a simulation with multiple strategies:
import randomimport… Read the full blog for free on Medium.
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