JOURNAL ARTICLE

Automated mechanism design with co-evolutionary hierarchical genetic programming techniques

Abstract

We present a novel form of automated game theoretic mechanism design in which mechanisms and players co-evolve. We also model the memetic propagation of strategies through a population of players, and argue that this process represents a more accurate depiction of human behavior than conventional economic models. The resulting model is evaluated by evolving mechanisms for the ultimatum game, and replicates the results of empirical studies of human economic behaviors, as well as demonstrating the ability to evaluate competing hypothesizes for the creation of economic incentives.

Keywords:
Mechanism (biology) Computer science Ultimatum game Mechanism design Population Incentive Genetic programming Game theory Process (computing) Evolutionary game theory Artificial intelligence Microeconomics Economics

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Topics

Experimental Behavioral Economics Studies
Social Sciences →  Social Sciences →  Safety Research
Game Theory and Applications
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Evolutionary Game Theory and Cooperation
Social Sciences →  Social Sciences →  Sociology and Political Science
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