Binding and Cross-modal Learning in Markov Logic Networks
Proceedings of Electrotechnical and Computer Science Conference ERK 2010, 2010
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 an 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 and a cross-modal learner in Markov logic network and test the system on a synthetic object database.