An Evolutionary Model of Bounded Rationality and Intelligence
Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia-it underlies current macroeconomic...
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| Published in | PloS one Vol. 7; no. 11; p. e50310 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
21.11.2012
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0050310 |
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| Summary: | Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia-it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions.
Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions.
Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that arise from natural selection. The key to understanding which types of behavior are more likely to survive is how behavior affects reproductive success in a given population's environment. From this perspective, intelligence is naturally defined as behavior that increases the probability of reproductive success, and bounds on rationality are determined by physiological and environmental constraints. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Conceived and designed the experiments: TB AL. Performed the experiments: TB AL. Analyzed the data: TB AL. Contributed reagents/materials/analysis tools: TB AL. Wrote the paper: TB AL. Competing Interests: The authors declare the following competing interests. Andrew W. Lo has the following affiliations and research grants: AlphaSimplex Group, LLC, Chairman and Chief Investment Strategist; U.S. Treasury (Office of Financial Research), Consultant; National Bureau of Economic Research, Research Associate; NY Fed Financial Advisory Roundtable, Member; FINRA Economic Advisory Committee, Member; Consortium for Systemic Risk Analysis, Academic Advisory Committee, Member; Beth Israel Deaconess Medical Center Board of Overseers, Member; research grant from the National Science Foundation on systemic risk; research grant from Citigroup; patent pending on cryptographic methods for computing systemic risk; patent awarded (U.S. Patent No. 7,599,876, “Electronic Market-Maker”); patent awarded (U.S. Patent No.7,562,042, “Data Processor for Implementing Forecasting Algorithms”). According to PLOS ONE, a competing interest is “anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision making, or publication of research or non-research articles submitted to one of the journals.” None of the above affiliations are remotely involved with the subject of the submission to PLOS ONE, nor do they or the authors stand to gain from the publication of this manuscript in PLOS ONE. Moreover, these affiliations do not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials. |
| ISSN: | 1932-6203 1932-6203 |
| DOI: | 10.1371/journal.pone.0050310 |