creators_name: Goldenberg, Eldan
creators_name: Garcowski, Jacob R
creators_name: Beer, Randall D
editors_name: Schaal, Stefan
editors_name: Ijspeert, Auke
editors_name: Billard, Aude
editors_name: Vijayakumar, Sethu
editors_name: Hallam, John
editors_name: Meyer, Jean-Arcady
type: confpaper
datestamp: 2006-07-01
lastmod: 2011-03-11 08:56:28
metadata_visibility: show
title: May We Have Your Attention: Analysis of a Selective Attention Task
ispublished: pub
subjects: comp-sci-mach-dynam-sys
subjects: comp-sci-art-intel
full_text_status: public
abstract: In this paper we present a deeper analysis than has previously been carried out of a selective attention problem, and the evolution of continuous-time recurrent neural networks to solve it. We show that the task has a rich structure, and agents must solve a variety of subproblems to perform well. We consider the relationship between the complexity of an agent and the ease with which it can evolve behavior that generalizes well across subproblems, and demonstrate a shaping protocol that improves generalization.
date: 2004
date_type: published
publisher: MIT Press (Bradford Books)
pagerange: 49-56
refereed: TRUE
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citation:   Goldenberg, Eldan and Garcowski, Jacob R and Beer, Randall D  (2004) May We Have Your Attention: Analysis of a Selective Attention Task.  [Conference Paper]     
document_url: http://cogprints.org/4950/1/GoldenbergGarcowskiSAB04.pdf