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Related papers: Emergent Dynamics in Neural Cellular Automata

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Methods for analyzing representations in neural systems have become a popular tool in both neuroscience and mechanistic interpretability. Having measures to compare how similar activations of neurons are across conditions, architectures,…

Machine Learning · Computer Science 2024-12-24 Quentin Guilhot , Michał Wójcik , Jascha Achterberg , Rui Ponte Costa

Number-conserving (or {\em conservative}) cellular automata have been used in several contexts, in particular traffic models, where it is natural to think about them as systems of interacting particles. In this article we consider several…

Cellular Automata and Lattice Gases · Physics 2007-05-23 Andres Moreira , Nino Boccara , Eric Goles

Most of the Neural Cellular Automata (NCAs) defined in the literature have a common theme: they are based on regular grids with a Moore neighborhood (one-hop neighbour). They do not take into account long-range connections and more complex…

Artificial Intelligence · Computer Science 2026-04-03 Léo Pio-Lopez , Benedikt Hartl , Michael Levin

We present a method of generating diverse collections of neural cellular automata (NCA) to design video game levels. While NCAs have so far only been trained via supervised learning, we present a quality diversity (QD) approach to…

Neural and Evolutionary Computing · Computer Science 2022-02-21 Sam Earle , Justin Snider , Matthew C. Fontaine , Stefanos Nikolaidis , Julian Togelius

A Cellular Automata (CA) rule is presented that can generate "loop patterns" in a 2D grid under fixed boundary conditions. A loop is a cyclically closed path represented by one-cells enclosed by zero-cells. A loop pattern can contain…

Cellular Automata and Lattice Gases · Physics 2025-05-30 Rolf Hoffmann , Mariusz Białecki

A stochastic cellular automata (CA) model for pedestrian dynamics is presented. Our goal is to simulate different types of pedestrian movement, from regular to panic. But here we emphasize regular situations which imply that pedestrians…

Mathematical Physics · Physics 2009-09-30 Ekaterina Kirik , Tat'yana Yurgel'yan , Dmitriy Krouglov

Memristors are novel non volatile devices that manage to combine storing and processing capabilities in the same physical place.Their nanoscale dimensions and low power consumption enable the further design of various nanoelectronic…

Since their inception at {\it Macy conferences} in later 1940s complex systems remain the most controversial topic of inter-disciplinary sciences. The term `complex system' is the most vague and liberally used scientific term. Using…

Cellular Automata and Lattice Gases · Physics 2014-06-10 Genaro J. Martinez , Andrew Adamatzky , Ramon Alonso-Sanz

Neuro-inspired models and systems have great potential for applications in unconventional computing. Often, the mechanisms of biological neurons are modeled or mimicked in simulated or physical systems in an attempt to harness some of the…

Neural and Evolutionary Computing · Computer Science 2021-10-18 Jørgen Jensen Farner , Håkon Weydahl , Ruben Jahren , Ola Huse Ramstad , Stefano Nichele , Kristine Heiney

We study the class of asynchronous non-uniform cellular automata (ANUCA) over an arbitrary group universe with multiple local transition rules. We introduce the notion of stable injectivity, stable reversibility, stable post-surjectivity…

Dynamical Systems · Mathematics 2022-03-03 Xuan Kien Phung

Substantial efforts have been applied to engineer CA with desired emergent properties, such as supporting gliders. Recent work in continuous CA has generated a wide variety of compelling bioreminiscent patterns, and the expansion of CA…

Neural and Evolutionary Computing · Computer Science 2022-05-25 Q. Tyrell Davis , Josh Bongard

Recurrent Neural Networks (RNNs) have shown great success in modeling time-dependent patterns, but there is limited research on their learned representations of latent temporal features and the emergence of these representations during…

Machine Learning · Computer Science 2023-06-13 Peter DelMastro , Rushiv Arora , Edward Rietman , Hava T. Siegelmann

The vulnerability to adversarial perturbations is a major flaw of Deep Neural Networks (DNNs) that raises question about their reliability when in real-world scenarios. On the other hand, human perception, which DNNs are supposed to…

Machine Learning · Computer Science 2023-08-09 Muhammad Ahmed Shah , Bhiksha Raj

Cyclic cellular automata (CCA) are models of excitable media. Started from random initial conditions, they produce several different kinds of spatial structure, depending on their control parameters. We introduce new tools from information…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Cosma Rohilla Shalizi , Kristina Lisa Shalizi

A general mathematical method is presented for the systematic construction of coupled map lattices (CMLs) out of deterministic cellular automata (CAs). The entire CA rule space is addressed by means of a universal map for CAs that we have…

Cellular Automata and Lattice Gases · Physics 2016-06-09 Vladimir García-Morales

Accurate chemical kinetics modeling is essential for combustion simulations, as it governs the evolution of complex reaction pathways and thermochemical states. In this work, we introduce Kinetic-Mamba, a Mamba-based neural operator…

Machine Learning · Computer Science 2026-04-07 Additi Pandey , Liang Wei , Hessam Babaee , George Em Karniadakis

The Cellular Automaton (CA) modeling and simulation of solid dynamics is a long-standing difficult problem. In this paper we present a new two-dimensional CA model for solid dynamics. In this model the solid body is represented by a set of…

Cellular Automata and Lattice Gases · Physics 2015-06-12 Yinfeng Dong , Guangcai Zhang , Aiguo Xu , Yanbiao Gan

Cellular automata (CA), originally developed as computational models of natural processes, have become a central subject in the study of complex systems and generative visual forms. Among them, the Ulam-Warburton Cellular Automaton (UWCA)…

Cellular Automata and Lattice Gases · Physics 2026-01-28 Chung-En Hao , Ivan C. H. Liu

The quintessential property of neuronal systems is their intensive patterns of selective synaptic connections. The current work describes a physics-based approach to neuronal shape modeling and synthesis and its consideration for the…

Neurons and Cognition · Quantitative Biology 2009-11-10 Luciano da Fontoura Costa , Regina Celia Coelho

Cellular Automata (CA) are discrete dynamical systems and an abstract model of parallel computation. The limit set of a cellular automaton is its maximal topological attractor. A well know result, due to Kari, says that all nontrivial…

Dynamical Systems · Mathematics 2009-02-10 Pietro Di Lena , Luciano Margara
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