Hey Pentti, We Did It!: A Fully Vector-Symbolic Lisp
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Abstract (arXiv)
Kanerva (2014) suggested that it would be possible to construct a complete Lisp out of a vector-symbolic architecture. We present the general form of a vector-symbolic representation of the five Lisp elementary functions, lambda expressions, and other auxiliary functions, found in the Lisp 1.5 specification McCarthy (1960), which is near minimal and sufficient for Turing-completeness. Our specific implementation uses holographic reduced representations Plate (1995), with a lookup table cleanup memory. Lisp, as all Turing-complete languages, is a Cartesian closed category, unusual in its proximity to the mathematical abstraction. We discuss the mathematics, the purpose, and the significance of demonstrating vector-symbolic architectures' Cartesian-closure, as well as the importance of explicitly including cleanup memories in the specification of the architecture.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 8 of its 39 references that are in the map. First posted on arXiv 18 Oct 2025.
Builds on
8 of 39 references.
References · 8
- 2020Hopfield Networks is All You Needcited by 461
- 2023Consciousness in Artificial Intelligence: Insights from the Science of Consciousnesscited by 99
- 2021A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformationscited by 98
- 2021A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challengescited by 68
- 2023Codebook Features: Sparse and Discrete Interpretability for Neural Networkscited by 45
- 2022Neurocompositional computing: From the Central Paradox of Cognition to a new generation of AI systemscited by 44
- 2022Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architecturescited by 17
- 2022Maze Learning using a Hyperdimensional Predictive Processing Cognitive Architecturecited by 4
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Citing papers per year: 2025: 2.
2 papers.