BoltzCONS: Dynamic Symbol Structures in a Connectionist Network

By D. Touretzky. 1990

Abstract BoltzCONS is a connectionist model that dynamically creates and manipulates composite symbol structures. These structures are implemented using a functional analog of linked lists, but BoltzCONS employs distributed representations and associative retrieval in place of a conventional memory organization. Associative retrieval leads to some interesting properties, e.g., the model can instantaneously access any uniquely-named internal node of a tree. But the point of the work is not to reimplement linked lists in some peculiar new way; it is to show how neural networks can exhibit compositionality and distal access (the ability to reference a complex structure via an abbreviated tag), two properties that distinguish symbol processing from lower-level cognitive functions such as pattern recognition. Unlike certain other neural net models, BoltzCONS represents objects as a collection of superimposed activity patterns rather than as a set of weights. It can therefore create new structured objects dynamically, without reliance on iterative training procedures, without rehearsal of previously-learned patterns, and without resorting to grandmother cells.

Subfields: Model Architectures

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Citations in the corpus

Neural Turing Machines (2014, background): “In response to this criticism, neural network researchers including Hinton (Hinton, 1986), Smolensky (Smolensky, 1990), Touretzky (Touretzky, 1990), Pollack (Pollack, 1990), Plate (Plate, 2003), and Kanerva (Kanerva, 2009) investigated specific mechanisms that could support both variable-binding and”
Learning Recursive Distributed Representations for Holistic Computation (1991, background): “The best example of such use is BoltzCONS [Touretzky, 1990].”
How Limited Systematicity Emerges: A Computational Cognitive Neuroscience Approach (Author's Manuscript) (2014, background): “Few connectionist researchers have shown much enthusiasm for the project of merely implementing a symbolic system, although proof-of-concept demonstrations do exist (Touretzky, 1990).”
Mapping Part-Whole Hierarchies into Connectionist Networks (1990, background): “Touretzky [30, 31] shows how this kind of working memory can be used to traverse and transform tree structures.”