Paper Info
Title
Manipulating space: modelling the role of transient dynamics in inattentional blindness
Abstract
According to Noe's enactive theory of perception, sensorimotor knowledge allows us to predict the sensory outcomes of our actions. This paper suggests that tuning input filters with such predictions may be the cause of sustained inattentional blindness. Most models of learning capture statistically salient regularities in and between data streams. Such analysis is, however, severely limited by both the problem of marginal regularity and the credit assignment problem. A neurocomputational reservoir system can be used to alleviate these problems without training by enhancing the separability of regularities in input streams. However, as the regularities made separable vary with the state of the reservoir, feedback in the form of predictions of future sensory input can both enhance expected discriminations and hinder unanticipated ones. This renders the model blind to features not made separable in the regions of state space the reservoir is manipulated towards. This is demonstrated in a computational model of sustained inattentional blindness, leading to predictions about human behaviour that have yet to be tested.
Year
DOI
Venue
2009
10.1080/09540090902924025
CONNECTION SCIENCE
Keywords
Field
DocType
sensorimotor learning,inattentional blindness,linear separation,transient dynamics,anticipation,enactive perception,reservoir systems
Data stream mining,Inattentional blindness,Anticipation,Computer science,Separable space,Artificial intelligence,Perception,State space,Machine learning,Information and Computer Science,Salient
Journal
Volume
Issue
ISSN
21.0
SP4
0954-0091
Citations 
PageRank 
References 
3
0.48
10
Authors
3
Name
Order
Citations
PageRank
Anthony F. Morse1162.73
Robert Lowe211112.22
Tom Ziemke368167.03