ASSC7 ABSTRACT

Modeling Memory Systems with Global Workspace Theory

By Uma Ramamurthy, Sidney K. D'Mello and Stan Franklin

Human memory seems to come in myriad of versions: sensory memory, working memory, transient episodic memory, autobiographical memory, semantic memory and procedural memory. This research attempts to computationally model these memory systems and their relationship to consciousness in the context of an existing software agent, IDA (Intelligent Distribution Agent). IDA implements Baars' global workspace theory of consciousness. We implement some of the memory systems in IDA with Kanerva's Sparse Distributed Memory architecture.

Using the IDA model, we are attempting to computationally test several hypotheses that serve to simplify relationships between the various types of memory and their relationship to consciousness. We hypothesize that Working Memory contents cue retrieval of local associations from Transient Episodic Memory and Long-Term Memory; an attention mechanism selects the contents of consciousness from the contents of Working Memory and these local associations; and only conscious contents are stored in Transient Episodic Memory and hence, Long Term Memory, due to the consolidation process from Transient Episodic Memory to Long Term Memory.

This research is aimed at better understanding of memory systems, and the relationship between memory and consciousness.