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== Reference ==
 
== Reference ==
Shashank Bhatia and Stephan Chalup: [[A Model of Heteroassociative Memory: Deciphering Surprising Features and Locations]]. In: [[Computational Creativity 2013 ICCC 2013]], 131-138.  
+
Shashank Bhatia and Stephan Chalup: [[A Model of Heteroassociative Memory: Deciphering Surprising Features and Locations]]. In: [[Computational Creativity 2013 ICCC 2013]], 139-146.  
  
 
== DOI ==
 
== DOI ==
Zeile 46: Zeile 46:
 
  month = {Jun},
 
  month = {Jun},
 
  location = {Sydney, New South Wales, Australia},
 
  location = {Sydney, New South Wales, Australia},
  pages = {131-138},
+
  pages = {139-146},
 
  url = {http://www.computationalcreativity.net/iccc2013/download/iccc2013-bhatia-chalup.pdf, http://de.evo-art.org/index.php?title=A_Model_of_Heteroassociative_Memory:_Deciphering_Surprising_Features_and_Locations },
 
  url = {http://www.computationalcreativity.net/iccc2013/download/iccc2013-bhatia-chalup.pdf, http://de.evo-art.org/index.php?title=A_Model_of_Heteroassociative_Memory:_Deciphering_Surprising_Features_and_Locations },
 
  publisher = {International Association for Computational Creativity},
 
  publisher = {International Association for Computational Creativity},

Version vom 12. November 2015, 23:19 Uhr


Reference

Shashank Bhatia and Stephan Chalup: A Model of Heteroassociative Memory: Deciphering Surprising Features and Locations. In: Computational Creativity 2013 ICCC 2013, 139-146.

DOI

Abstract

The identification of surprising or interesting locations in an environment is an important problem in the fields of robotics (localisation, mapping and exploration), ar- chitecture (wayfinding, design), navigation (landmark identification) and computational creativity. Despite this familiarity, existing studies are known to rely ei- ther on human studies (in architecture and navigation) or complex feature intensive methods (in robotics) to evaluate surprise. In this paper, we propose a novel het- eroassociative memory architecture that remembers in- put patterns along with features associated with them. The model mimics human memory by comparing and associating new patterns with existing patterns and fea- tures, and provides an account of surprise experienced. The application of the proposed memory architecture is demonstrated by identifying monotonous and surprising locations present in a Google Sketchup model of an en- vironment. An inter-disciplinary approach combining the proposed memory model and isovists (from archi- tecture) is used to perceive and remember the structure of different locations of the model environment. The experimental results reported describe the behaviour of the proposed surprise identification technique, and illus- trate the universal applicability of the method. Finally, we also describe how the memory model can be modi- fied to mimic forgetfulness.

Extended Abstract

Bibtex

@inproceedings{
author = {Shashank Bhatia and Stephan Chalup},
title = {A Model of Heteroassociative Memory: Deciphering Surprising Features and Locations},
editor = {Simon Colton, Dan Ventura, Nada Lavrac, Michael Cook},
booktitle = {Proceedings of the Fourth International Conference on Computational Creativity},
series = {ICCC2013},
year = {2013},
month = {Jun},
location = {Sydney, New South Wales, Australia},
pages = {139-146},
url = {http://www.computationalcreativity.net/iccc2013/download/iccc2013-bhatia-chalup.pdf, http://de.evo-art.org/index.php?title=A_Model_of_Heteroassociative_Memory:_Deciphering_Surprising_Features_and_Locations },
publisher = {International Association for Computational Creativity},
keywords = {computational, creativity},
}

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