Combining Experimental and Theoretical Evidence to Understand Predator Learning Behaviour with Unfamiliar Prey | Zendy

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Combining Experimental and Theoretical Evidence to Understand Predator Learning Behaviour with Unfamiliar Prey

Author(s) -

Lauren Efford

Publication year - 2019

Language(s) - English

Resource type - Dissertations/theses

DOI - 10.22215/etd/2019-13809

Subject(s) - predation , predator , selection (genetic algorithm) , prior probability , artificial intelligence , bayesian inference , sampling (signal processing) , ecology , bayesian probability , machine learning , biology , computer science , computer vision , filter (signal processing)

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