3 papers
cs.LG2026
It's Much Easier for Neural Networks to learn Game of Life Dynamics with the Right Activation Function: Polynomial Kolmogorov-Arnold Networks
Tashin Ahmed, Q. Tyrell Davis
Previous work has found a gap between the scale of neural networks that reliably learn Conway's Game of Life, and minimal networks capable of representing the classic cellular auto…
nlin.CG2024
Non-Platonic Autopoiesis of a Cellular Automaton Glider in Asymptotic Lenia
Q. Tyrell Davis
Like Life, Lenia CA support a range of patterns that move, interact with their environment, and/or are modified by said interactions. These patterns maintain a cohesive, self-organ…
nlin.CG2024
Discretization-Dependent Dissolution of (Dis)Continuous Gliders: Non-Platonic Self-Organization in Complex Systems
Q. Tyrell Davis
Many simulated complex systems that support persistent self-organizing patterns, i.e. gliders, have a 'state-plus-update' paradigm. This approach can be found in computational mode…