Affiliation:
1. University of Maryland, College Park, MD
Abstract
Researchers have invested much effort in constructing models of the state-dependent (sometimes risk-averse and sometimes risk-prone) nature of human decision making. An important open question is how state-dependent risk behavior can arise and remain prominent in populations. We believe that one part of the answer is the interplay between risk-taking and sequentiality of choices in populations subject to evolutionary population dynamics. To support this hypothesis, we provide simulation and analytical results for evolutionary lottery games, including results on evolutionary stability. We consider a parameterized class of
imitation dynamics
in which the parameter 0 ≤ α ≤ 1 yields the
replicator dynamic
with α = 1 and the
imitate-the-better
dynamic with α = 0. Our results demonstrate that for every population dynamic in this class except for the replicator dynamic, the interplay between risk-taking and sequentiality of choices allows state-dependent risk behavior to have an evolutionary advantage over expected-value maximization.
Funder
Army Research Office
Air Force Office of Scientific Research
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Theoretical Computer Science
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