Modeling binding and cross-modal learning in Markov logic networks

Authors:
Alen VrečKo;Aleš Leonardis;Danijel SkočAj
Affiliations:
Faculty of Computer and Information Science, University of Ljubljana, Traška 25, 1000 Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Traška 25, 1000 Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Traška 25, 1000 Ljubljana, Slovenia
Venue:
Neurocomputing
Year:
2012

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Abstract

Binding - the ability to combine two or more modal representations of the same entity into a single shared representation - is vital for every cognitive system operating in a complex environment. In order to successfully adapt to changes in a dynamic environment the binding mechanism has to be supplemented with cross-modal learning. In this paper we define the problems of high-level binding and cross-modal learning. By these definitions we model a binding mechanism in a Markov logic network and define its role in a cognitive architecture. We evaluate a prototype binding system off-line, using three different inference methods.