Matches in UGent Biblio for { <https://biblio.ugent.be/publication/680344#aggregation> ?p ?o. }
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- aggregation classification "P1".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2008".
- aggregation hasFormat 680344.bibtex.
- aggregation hasFormat 680344.csv.
- aggregation hasFormat 680344.dc.
- aggregation hasFormat 680344.didl.
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- aggregation isPartOf urn:isbn:978-1-4244-1646-2.
- aggregation isPartOf urn:issn:1050-4729.
- aggregation language "eng".
- aggregation publisher "IEEE".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Technology and Engineering".
- aggregation title "Mobile Robot Control in the Road Sign Problem using Reservoir Computing Networks".
- aggregation abstract "In this work we tackle the road sign problem with Reservoir Computing (RC) networks. The T-maze task (a particular form of the road sign problem) consists of a robot in a T-shaped environment that must reach the correct goal (left or right arm of the T-maze) depending on a previously received input sign. It is a control task in which the delay period between the sign received and the required response (e.g., turn right or left) is a crucial factor. Delayed response tasks like this one form a temporal problem that can be handled very well by RC networks. Reservoir Computing is a biologically plausible technique which overcomes the problems of previous algorithms such as Backpropagation Through Time - which exhibits slow (or non-) convergence on training. RC is a new concept that includes a fast and efficient training algorithm. We show that this simple approach can solve the T-maze task efficiently.".
- aggregation authorList BK82753.
- aggregation endPage "916".
- aggregation startPage "911".
- aggregation isDescribedBy 680344.
- aggregation similarTo LU-680344.