Vector LIDA

Abstract

The representation paradigm used by a cognitive architecture helps to determine the kind of processes that it can perform more efficiently. Vector LIDA is a variation of the LIDA cognitive architecture that employs high-dimensional Modular Composite Representation (MCR) vectors as its main representation model and Integer Sparse Distributed Memory as its main memory implementation technology. The advantages of this new model include a more realistic and biologically plausible model, better integration with its episodic memory, better integration with other low level perceptual processing (such as deep learning systems), better scalability, and easier learning mechanisms. Here, after briefly recapping the LIDA model and MCR, we describe Vector LIDA and argue for its several advantages.