Evolution of Risk Aversion in Adaptive Learning Agents
Risk aversion is one of the most commonly cited properties of human decision making (e.g., Kahneman & Tversky, 1979). This finding is at odds with traditional expected value theory, but not with more recent theories of rational choice (e.g., von Neumann & Morgenstern, 1944). Since Bernoulli?s solution of the St. Petersburg paradox by appeal to marginally decreasing sensitivity to money (his so-called ?moral expectation?), there has been a debate as to the rationality of this apparent risk aversion. Rather than evaluating rationality by appealing to notions of consistency (as is often done), another, I think, more satisfying approach is to evaluate the survival/adaptive advantage conferred on an individual who exhibits particular behaviors: If one finds that a behavior x gives a greater survival advantage than behavior y, then, one can reasonably argue, the latter is more rational than the former. To investigate the adaptive advantage of different risk preferences, I used a replicator dynamic to model the evolution of populations of adaptive learning agents (Roth-Erev machines) in repeated coordination games. Risk aversion consistently displaced risk seeking and risk neutral behavior in the populations, and, as a result, the populations evolved to prefer the risk dominant (inefficient) equilibrium point. These results support the argument that risk aversion (at least for gains) is a rational property of adaptive learning agents (and, by extension, of people).
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||01 Apr 2001|
|Date of revision:|
|Contact details of provider:|| Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html|
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:sce:scecf1:253. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.