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== Reference ==
 
== Reference ==
Philip Galanter: Computational Aesthetic Evaluation: Past and Future. In: McCormack & d’Inverno: Computers and Creativity, Springer, Berlin, 2012, 255-293  
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[[Philip Galanter]]: Computational Aesthetic Evaluation: Past and Future. In: McCormack & d’Inverno: Computers and Creativity, Springer, Berlin, 2012, 255-293  
  
 
== DOI ==
 
== DOI ==
Zeile 13: Zeile 11:
  
 
== Bibtex ==  
 
== Bibtex ==  
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@incollection{
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year={2012},
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isbn={978-3-642-31726-2},
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booktitle={Computers and Creativity},
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editor={McCormack, Jon and d’Inverno, Mark},
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doi={10.1007/978-3-642-31727-9_10},
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title={Computational Aesthetic Evaluation: Past and Future},
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url={http://dx.doi.org/10.1007/978-3-642-31727-9_10 http://de.evo-art.org/index.php?title=Computational_Aesthetic_Evaluation:_Past_and_Future },
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publisher={Springer Berlin Heidelberg},
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author={Galanter, Philip},
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pages={255-293},
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language={English}
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}
  
 
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== Used References ==
 
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Aktuelle Version vom 3. November 2015, 13:35 Uhr

Reference

Philip Galanter: Computational Aesthetic Evaluation: Past and Future. In: McCormack & d’Inverno: Computers and Creativity, Springer, Berlin, 2012, 255-293

DOI

http://link.springer.com/chapter/10.1007/978-3-642-31727-9_10

Abstract

Human creativity typically includes a self-critical aspect that guides innovation towards a productive end. This chapter offers a brief history of, and outlook for, computational aesthetic evaluation by digital systems as a contribution towards potential machine creativity. First, computational aesthetic evaluation is defined and the difficult nature of the problem is outlined. Next, a brief history of computational aesthetic evaluation is offered, including the use of formulaic and geometric theories; design principles; evolutionary systems including extensions such as coevolution, niche construction, agent swarm behaviour and curiosity; artificial neural networks and connectionist models; and complexity models. Following this historical review, a number of possible contributions towards future computational aesthetic evaluation methods are noted. Included are insights from evolutionary psychology; models of human aesthetics from psychologists such as Arnheim, Berlyne, and Martindale; a quick look at empirical studies of human aesthetics; the nascent field of neuroaesthetics; new connectionist computing models such as hierarchical temporal memory; and computer architectures for evolvable hardware. Finally, it is suggested that the effective complexity paradigm is more useful than information or algorithmic complexity when thinking about aesthetics.

Extended Abstract

Bibtex

@incollection{
year={2012},
isbn={978-3-642-31726-2},
booktitle={Computers and Creativity},
editor={McCormack, Jon and d’Inverno, Mark},
doi={10.1007/978-3-642-31727-9_10},
title={Computational Aesthetic Evaluation: Past and Future},
url={http://dx.doi.org/10.1007/978-3-642-31727-9_10 http://de.evo-art.org/index.php?title=Computational_Aesthetic_Evaluation:_Past_and_Future },
publisher={Springer Berlin Heidelberg},
author={Galanter, Philip},
pages={255-293},
language={English}
}

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