AI Reading List: Vector Symbolic Architectures, Attention, and other approaches

Below is a portion of my informal list of readings related to Artificial Intelligence (AI). This started out as a very short list created for use in conjunction with an academic presentation and has now grown much larger. Please let me know if you have any corrections, additions, suggestions, etc. It is very idiosyncratic and not meant to be comprehensive. Please feel free to share with others.

Artificial Intelligence (AI) Reading List, by Philip Rubin

Vector Symbolic Architectures, Attention, and other approaches:

Myriam Wares. A New Approach to Computation Reimagines Artificial Intelligence. Quanta Magazine, Apr. 13, 2023.  

Trenton Bricken and Cengiz Pehlevan. Attention Approximates Sparse Distributed Memory. arXiv:2111.05498, Jan. 17, 2022.

Kenny Schlegel, Peer Neubert, and Peter Protzel. A comparison of Vector Symbolic Architectures. arXiv:2001.11797, 2021

Charles W. Lowney II, Simon D. Levy, William Meroney, and Ross W. Gayler. Connecting Twenty-First Century Connectionism and WittgensteinPhilosophia48, 643–671, 2020

Ashish Vashwani, et al. Attention is all you need. arXiv:1706.03762v5 7 Dec 2017.

Rasmussen, D. and Eliasmith, C. A neural model of rule generation in inductive reasoning. Topics in Cognitive Science, 3, 140-153, 2011.

Ross W. Gayler, Simon D. Levy, and Rens Bod. Explanatory Aspirations and the Scandal of Cognitive NeuroscienceProceedings of the First Annual Meeting of the BICA Society, August 2010, 42-51. 2010

Ross W. Gayler and Simon D. Levy. A Distributed Basis For Analogical Mapping. Conference paper. 2009

Pentti Kanerva. Hyperdimensional computing: An Introduction to Computing in Distributed Representation with High-Dimensional Random Vectors. Cognitive Computation, 1, 139-159, 2009

Ross Gayler. Vector Symbolic Architectures answer Jackendoff's challenges for cognitive neuroscience. Semantic Scholar, Corpus ID: 5943414, Dec. 13, 2004. In P. Slezak (Ed.), ICCS/ASCS international conference on cognitive science, pp. 133-138. Sydney Australia, University of New South Wales: CogPrints. 2003

Tony A. Plate. Holographic reduced representation: Distributed representation for cognitive structures. University of Chicago Press: 2003

Dmitri A. Rachkovskij, and Ernst M. Kussul, Binding and normalization of binary sparse distributed representations by context-dependent thinning. Neural Computation,13(2), 411–452. 2001. DOI 10.1162/ 089976601300014592

Tony A. Plate. A common framework for distributed representation schemes for compositional structure. Connectionist Systems for Knowledge Representations and Deduction (July), 15–34.1997

Paul Smolensky. Tensor product variable binding and the representation of symbolic structures in connectionist systems. Artificial Intelligence, 46, 159-216. 1990

< AI Reading List >