Show simple item record Hülse, Martin Lee, Mark
dc.contributor.editor Chappell, J.
dc.contributor.editor Thorpe, S.
dc.contributor.editor Hawes, N.
dc.contributor.editor Sloman, A. 2010-09-22T15:35:16Z 2010-09-22T15:35:16Z 2010-04
dc.identifier.citation Hülse , M & Lee , M 2010 , The Logic of Biological Inspired Robotics . in J Chappell , S Thorpe , N Hawes & A Sloman (eds) , Proceedings of the International Symposium on AI-Inspired Biology . pp. 43 - 50 , International Symposium on AI-Inspired Biology , Leicester , United Kingdom of Great Britain and Northern Ireland , 29 Mar 2010 . en
dc.identifier.citation conference en
dc.identifier.other PURE: 1166698
dc.identifier.other PURE UUID: 39971304-4909-47d7-89d0-d9959bf2d9aa
dc.identifier.other dspace: 2160/5697
dc.identifier.other DSpace_20121128.csv: row: 3661
dc.identifier.other 2160/5697
dc.description Huelse, M., Lee, M.: The logic of biological inspired robotics.In: Proceedings of the International Symposium on AI-Inspired Biology, Chappell, J., Thorpe, S., Hawes, N., Sloman, A. (Eds.) at the AISB 2010 convention, 29 March - 1 April 2010, De Montfort University, Leicester, UK, pp. 43 - 50. Sponsorship: EPSRC en
dc.description.abstract Biologically inspired robotics is a well known approach for the design of autonomous intelligent robot systems. Very often it is assumed that biologically inspired models successfully implemented on robots offer new scientific knowledge for biology too. In other words, robots experiments serving as a replacement for the biological system under investigation are assumed to provide new scientific knowledge for biology. This article is a critical investigation of this assumption. We begin by clarifying what we mean by 'new scientific knowledge.' Following Karl Popper's work the The Logic of Scientific Discovery we conclude that in general robotic experiments serving as replacement for biological systems can never directly deliver any new scientific knowledge for biology. We further argue that there is no formal guideline which defines the level of 'biological plausibility' for biologically inspired robot implementations. Therefore, there is no reason to prefer some kind of robotic setup before others. Any claimed relevance for biology, however, is only justified if results from robotic experiments are translated back into new models and hypotheses amenable to experimental tests within the domain of biology. This translation 'back' into biology is very often missing and we will discuss popular robotics frameworks in the context of Brain Research, Cognitive Science and Developmental Robotics in order to highlight this issue. Nonetheless, such frameworks are valuable and important, like pure mathematics, because they might lead to new formalisms and methods which in future might be essential for gaining new scientific knowledge if applied in biology. No one can tell, if and which of the current robotics frameworks will provide these new scientific tools. What we can already say–the main message of this article–is that robot systems serving as a replacement for biological systems won’t be sufficient for the test of biological models, i.e. gaining new scientific knowledge in biology. en
dc.format.extent 8 en
dc.language.iso eng
dc.relation.ispartof Proceedings of the International Symposium on AI-Inspired Biology en
dc.rights en
dc.title The Logic of Biological Inspired Robotics en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontobookanthology/conference en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Intelligent Robotics Group en

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