Paper: symbol processing, dynamic bindings, and temporal synchrony

[Lokendra Shastri]

Dear Connectionists,

The following preprint may be of interest to you. Best wishes.

-- Lokendra Shastri

http://www.icsi.berkeley.edu/~shastri/psfiles/shruti_adv_98.ps.gz

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        Advances in SHRUTI: A neurally motivated model of relational
    knowledge representation and rapid inference using temporal synchrony.

                              Lokendra Shastri
                  International Computer Science Institute
                             Berkeley, CA 94704

				Abstract

We are capable of drawing a variety of inferences effortlessly, spontaneously,
and with remarkable efficiency --- as though these inferences are a *reflex*
response of our cognitive apparatus. This remarkable human ability poses a
challenge for cognitive science and computational neuroscience: How can a
network of slow neuron-like elements represent a large body of systematic
knowledge and perform a wide range of inferences with such speed? 

The connectionist model SHRUTI attempts to address this challenge by 
demonstrating how a neurally plausible network can encode a large body of 
semantic and episodic facts, systematic rules, and knowledge about entities 
and types, and yet perform a wide range of explanatory and predictive 
inferences within a few hundred milliseconds. Relational structures (frames, 
schemas) are represented in SHRUTI by clusters of cells, and inference in 
SHRUTI corresponds to a transient propagation of rhythmic activity over such 
cell-clusters wherein *dynamic bindings* are represented by the synchronous 
firing of appropriate cells. SHRUTI encodes mappings across relational 
structures using high-efficacy links that enable the propagation of rhythmic
activity, and it encodes items in long-term memory as coincidence and
conincidence-error detector circuits that become active in response to the
occurrence (or non-occurrence) of appropriate coincidences in the on going
flux of rhythmic activity. Finally, ``understanding'' in SHRUTI corresponds
to reverberant and coherent activity along closed loops of neural circuitry.

Over the past several years, SHRUTI has undergone several enhancements that
have augmented its expressiveness and inferential power. This paper describes
some of these extensions that enable SHRUTI to (i) deal with negation and
inconsistent beliefs, (ii) encode evidential rules and facts, (iii) perform
inferences requiring the dynamic instantiation of entities, and (iv) seek
coherent explanations of observations.

Keywords: knowledge representation; inference;
	evidential reasoning; dynamic binding; temporal synchrony.

To appear in Applied Intelligence.