Ph.D. thesis announcement: Infinite RAAM

[Simon Levy]

Levy, Simon D. (2002). Infinite RAAM: Initial Investigations into a 
Fractal Basis for Cognition. Ph.D. Thesis, Brandeis University, July 2002.

Abstract

This thesis attempts to provide an answer to the question ``What is the 
mathematical basis of cognitive representations?'' The answer we present 
is a novel connectionist framework called Infinite RAAM. We show how 
this framework satisfies the cognitive requirements of systematicity, 
compositionality, and scalable representational capacity, while also 
exhibiting ``natural'' properties like learnability, generalization, and 
inductive bias. The contributions of this work are twofold: First, 
Infinite RAAM shows how connectionist models can exhibit infinite 
competence for interesting cognitive domains like language. Second, our 
attractor-based learning algorithm provides a way of learning structured 
cognitive representations, with robust decoding and generalization. Both 
results come from allowing the dynamics of the network to devise 
emergent representations during learning. An appendix provides Matlab 
code for the experiments described in the thesis.


Keywords: Neural Networks, Fractals, Connectionism, Language, Grammar.

Postscript: http://www.demo.cs.brandeis.edu/papers/levythesis.ps
Gzipped: http://www.demo.cs.brandeis.edu/papers/levythesis.ps.gz
PDF: http://www.demo.cs.brandeis.edu/papers/levythesis.pdf