Binding and Cross-modal Learning in Markov Logic Networks
Proceedings of the 2011 International Conference on Adaptive and Natural Computing Algorithms (ICANNGA'11), 2011
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.