Learning foraging thresholds for lizards: an analysis of a simple learning algorithm
UNSPECIFIED. (1999) Learning foraging thresholds for lizards: an analysis of a simple learning algorithm. JOURNAL OF THEORETICAL BIOLOGY, 197 (3). pp. 361-369. ISSN 0022-5193Full text not available from this repository.
This paper gives proof of convergence for a learning algorithm that describes how anoles (lizards found in the Caribbean) learn foraging threshold distance. An anole will pursue a prey if and only if it is within this threshold of the anole's perch. The learning algorithm was proposed by Roughgarden and his colleagues. They experimentally determined that this algorithm quickly converges to the foraging threshold that is predicted by optimal foraging theory. We provide analytic confirmation that the optimal foraging behavior as predicted by Roughgarden's model can be attained by a lizard that follows this simple and zoologically plausible rule of thumb. (C) 1999 Academic Press.
|Item Type:||Journal Article|
|Subjects:||Q Science > QH Natural history > QH301 Biology|
|Journal or Publication Title:||JOURNAL OF THEORETICAL BIOLOGY|
|Publisher:||ACADEMIC PRESS LTD|
|Date:||7 April 1999|
|Number of Pages:||9|
|Page Range:||pp. 361-369|
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