A comparison of ecological and evolutionary models of decisions under risk

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dc.contributor.author Hill, William Trey
dc.date.accessioned 2013-04-19T13:52:12Z
dc.date.available 2013-04-19T13:52:12Z
dc.date.issued 2013-04-19
dc.identifier.uri http://hdl.handle.net/2097/15531
dc.description.abstract Risky decision making occurs in both humans and non-human animals. For a large portion of the history of scientific investigation into human judgment and decision making, risky behavior has been viewed as flawed and irrational. However, the past several decades have seen advances in the view of human rationality. Scientists have suggested that, rather than using probability theory as the metric by which humans are judged as rational or irrational, human minds should be evaluated with respect to specific ecologies (e.g., Gigerenzer & Selten, 2001) with some scientists going further and specifying the ecologies as those which our ancestors evolved; essentially, our minds and their decision processes are adapted to solve specific recurring problems, and to solve those problems in specific environments. Within the domain of risky decision making there are a number of theories and models which are consistent with the hypothesis that human (and non-human) minds are molded for specific behavioral patterns based on environmental cues. One example is the priority heuristic. The priority heuristic is based in the ecological rationality approach—that heuristics are designed for specific ecologies. However, the ecological rationality of the priority heuristic is underspecified. Studies One and Two of the present dissertation compared predictions made by two models of risk-taking from evolutionary biology and behavioral ecology (dominance theory and risk-sensitive foraging) with a variety of predictions made by the priority heuristic. Data clearly showed that risk-sensitive foraging outperforms the priority heuristic (Study One) and that the priority heuristic cannot account for the motivation to acquire a minimum number of resources. Study Two showed mixed results for the priority heuristic when compared to dominance theory. Specifically, choice patterns were consistent with the priority heuristic, but process data in the form of decision times were not consistent with the priority heuristic. Also, the data pointed to a strong effect for desiring higher status when competing against others of varying status. Study Three compared four potential models of risky decision making in an attempt to extend the pattern of results from Studies One and Two showing general risk-sensitivity when attempting to achieve a specified need level (Money for Study One; Status for Study Two). Also, Study Three attempted to clarify the scope of the pattern of general risk-sensitivity by examining differential patterns of results based on whether the models predicted motivations to achieve need levels for money, status, or both. Results from Study Three were consistent with a general model of risk-sensitivity which operated on both monetary need levels and status need levels. This effect was additionally ubiquitous for males and females, contrary to predictions by dominance theory. The data from three studies showed support for a general model of risk-sensitivity consistent with those proposed by others (Mishra, 2010). The concept and implications of this general risk-sensitivity model are discussed, as well as future directions to understand the finer details and potential scope of this particular general risk-sensitivity model. en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Risky choice en_US
dc.subject Heuristics en_US
dc.subject Foraging theory en_US
dc.title A comparison of ecological and evolutionary models of decisions under risk en_US
dc.type Dissertation en_US
dc.description.degree Doctor of Philosophy en_US
dc.description.level Doctoral en_US
dc.description.department Department of Psychological Sciences en_US
dc.description.advisor Gary L. Brase en_US
dc.subject.umi Cognitive Psychology (0633) en_US
dc.date.published 2013 en_US
dc.date.graduationmonth May en_US

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