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