Ben-Gai, Lior. 2025. Laboratory of Babel — Explorations of Emergent Virtual Structures. Doctoral thesis, Goldsmiths, University of London [Thesis]

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Abstract or Description

Cellular Automata (CA) are discrete, grid-based computational models where simple local rules generate complex, emergent patterns. Despite decades of research, the vast potential of CA remains largely unexplored, with countless possible algorithms as yet undiscovered. This work introduces novel methods for open-ended exploration of CA, expanding the scope of inquiry to reveal virtual phenomena that might otherwise be overlooked.

A core contribution of this thesis is Utomata, a new computational framework designed for exploration and study of a wide range of CA. Its versatility is demonstrated through case studies featuring both established and novel algorithms. Building on this foundation, the thesis presents Spatial Mapping, a high-level exploration method, accompanied by a custom online software implementation. This method enables systematic navigation of the combinatorial space of variations for any given algorithm.

Central to this thesis is the introduction and in-depth study of Type-U, a newly identified CA family. Using the frameworks and methods developed, this study reveals distinctive properties of Type-U algorithms and their combinatorial spaces, supported by qualitative analyses. The thesis concludes by discussing the broader implications of this open-ended approach for the study of virtual phenomena and outlining avenues for future research.

Item Type:	Thesis (Doctoral)
Identification Number (DOI):	https://doi.org/10.25602/GOLD.00038810
Keywords:	Cellular Automata, Computational Arts, Artificial Life, Emergence, Algorithmic Exploration, Computational Modelling, Structure Synthesis, Procedural Content Generation, Abstraction, Functional Programming
Departments, Centres and Research Units:	Computing
Date:	30 April 2025
Item ID:	38810
Date Deposited:	13 May 2025 16:04
Last Modified:	13 May 2025 16:09
URI:	https://research.gold.ac.uk/id/eprint/38810

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