mlsanityData to 7 Oct 2026

Reinforcement Learning Produces Dominant Strategies for the Iterated Prisoner's Dilemma

arXiv 1707.06307 ↗First posted 19 Jul 2017cs.GTcited by 7

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Abstract (arXiv)

We present tournament results and several powerful strategies for the Iterated Prisoner's Dilemma created using reinforcement learning techniques (evolutionary and particle swarm algorithms). These strategies are trained to perform well against a corpus of over 170 distinct opponents, including many well-known and classic strategies. All the trained strategies win standard tournaments against the total collection of other opponents. The trained strategies and one particular human made designed strategy are the top performers in noisy tournaments also.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jul 2017.

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Citing papers per year: 2022: 2; 2023: 2; 2024: 2; 2025: 1.

7 papers.