The 2x2 Game

By A. Rapoport, M. Guyer, David G. Gordon. 1976

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Empirically Evaluating Multiagent Learning Algorithms (2014, methodology): “We drew an additional 100 instances from the last distribution, D13, which spans all strategically distinct 2 × 2 games (Rapoport et al., 1976).”
An Overview of Cooperative and Competitive Multiagent Learning (2005, background): “For a complete taxonomy we refer the reader to [132].”
Run the GAMUT: a comprehensive approach to evaluating game-theoretic algorithms (2004, methodology): “For example, we implemented a single generator based on work by Rapoport [15] which demonstrated that there are only 85 strategically different 2x2 games, and so did not need to implement generators for individual 2x2 games mentioned in the literature.”
Cooperating with machines (2017, background): “chine cooperation as a phenomenon that emerges from the interaction among self-interested parties [33], rather than by explicit design constraints programmed into domain-speciÞc computational systems [34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44]. Our results demonstrate that emergent cooperation betw”
A Continuous Dilemma âˆ (2009, background): “Strategy B is strictly dominant, and so (B,B) is the unique Nash equilibrium, as long as the “tempation” payoff satisfies x > 10.”