---
abstract: 'Neural network-based controllers are evolved for racing simulated R/C cars around several tracks of varying difficulty. The transferability of driving skills acquired when evolving for a single track is evaluated, and different ways of evolving controllers able to perform well on many different tracks are investigated. It is further shown that such generally proficient controllers can reliably be developed into specialized controllers for individual tracks. Evolution of sensor parameters together with network weights is shown to lead to higher final fitness, but only if turned on after a general controller is developed, otherwise it hinders evolution. It is argued that simulated car racing is a scalable and relevant testbed for evolutionary robotics research, and that the results of this research can be useful for commercial computer games.'
altloc:
- http://julian.togelius.com/Togelius2006Evolving.pdf
chapter: ~
commentary: ~
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confdates: 'July 16-21, 2006'
conference: IEEE Congress on Evolutionary Computation
confloc: 'Vancouver, Canada'
contact_email: ~
creators_id: []
creators_name:
- family: Togelius
given: Julian
honourific: ''
lineage: ''
- family: Lucas
given: Simon M.
honourific: ''
lineage: ''
date: 2006
date_type: published
datestamp: 2006-10-15
department: ~
dir: disk0/00/00/52/19
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eprintid: 5219
fileinfo: /style/images/fileicons/application_pdf.png;/5219/1/Togelius2006Evolving.pdf
full_text_status: public
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keywords: ~
lastmod: 2011-03-11 08:56:39
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metadata_visibility: show
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pubdom: FALSE
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publisher: IEEE Press
refereed: TRUE
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relation_type: []
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reportno: ~
rev_number: 12
series: ~
source: ~
status_changed: 2007-09-12 17:08:05
subjects:
- comp-sci-mach-learn
- comp-sci-neural-nets
- comp-sci-art-intel
succeeds: ~
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thesistype: ~
title: Evolving robust and specialized car racing skills
type: confpaper
userid: 4535
volume: ~