Two Models of Predator Decision Making Under Uncertainty

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  • Predators are faced with an uncertain world. The presence of anti-predator defences means that any potential prey item may actually be unpalatable, outright toxic, difficult to catch, or cause harm. In order to deal with this uncertainty regarding profitability, predators need strategies to make good decisions on what to attack based on the information about potential prey available to them. I develop two models of optimal decision making for predators. The first deals with generalizing from experience to novel prey types: I develop a Bayesian model framework that treats generalization as a process of learning about the distribution of prey in the environment, and apply it to a problem in generalization. The second deals with startle displays: I develop an extension of signal detection theory to cases where continued examination is possible, and apply it to predators faced with startle displays.

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  • Copyright © 2019 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
Date Created
  • 2019


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