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Here I report about the modifications of and relations between graphic lambda calculus, various formalisms which appeared under the name chemlambda and a version of directed interaction combinators. This is part of the study and experiments…

Logic in Computer Science · Computer Science 2020-07-21 Marius Buliga

Given a graph rewrite system, a graph G is a quine graph if it has a non-void maximal collection of non-conflicting matches of left patterns of graphs rewrites, such that after the parallel application of the rewrites we obtain a graph…

Artificial Intelligence · Computer Science 2020-04-01 Marius Buliga

We present chemlambda (or the chemical concrete machine), an artificial chemistry with the following properties: (a) is Turing complete, (b) has a model of decentralized, distributed computing associated to it, (c) works at the level of…

Artificial Intelligence · Computer Science 2019-02-20 Marius Buliga , Louis H. Kauffman

We propose the chemlambda artificial chemistry, whose behavior strongly suggests that real molecules which embed Interaction Nets patterns and real chemical reactions which resemble Interaction Nets graph rewrites could be a realistic path…

Emerging Technologies · Computer Science 2018-11-14 Marius Buliga

Recent advances and achievements of artificial intelligence (AI) as well as deep and graph learning models have established their usefulness in biomedical applications, especially in drug-drug interactions (DDIs). DDIs refer to a change in…

Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the origin of life. In this work we define a P system based artificial graph chemistry to understand the principles…

Neural and Evolutionary Computing · Computer Science 2009-01-06 Janardan Misra

One of the main goals of Artificial Life is to research the conditions for the emergence of life, not necessarily as it is, but as it could be. Artificial Chemistries are one of the most important tools for this purpose because they provide…

Adaptation and Self-Organizing Systems · Physics 2021-12-08 Germán Kruszewski , Tomas Mikolov

Artificial chemistry simulations produce many intriguing emergent behaviors, but they are often difficult to steer or control. This paper proposes a method for steering the dynamics of a classic artificial chemistry model, known as AlChemy…

Formal Languages and Automata Theory · Computer Science 2025-09-05 Devansh Vimal , Cole Mathis , Westley Weimer , Stephanie Forrest

Rapid discovery of new reactions and molecules in recent years has been facilitated by the advancements in high throughput screening, accessibility to a much more complex chemical design space, and the development of accurate molecular…

Molecular Networks · Quantitative Biology 2023-03-28 Vipul Mann , Venkat Venkatasubramanian

Gene Regulatory Networks are networks of interactions in biological organisms responsible for determining the production levels of proteins and peptides. Proteins are workers of a cell factory, and their production defines the goal of a…

Neural and Evolutionary Computing · Computer Science 2022-09-12 Iliya Miralavy , Wolfgang Banzhaf

Graph transformation formalisms have proven to be suitable tools for the modelling of chemical reactions. They are well established in theoretical studies and increasingly also in practical applications in chemistry. The latter is made…

Discrete Mathematics · Computer Science 2022-08-29 Jakob L. Andersen , Rolf Fagerberg , Juri Kolčák , Christophe V. F. P. Laurent , Daniel Merkle , Nikolai Nøjgaard

Robustness to a wide variety of negative factors and the ability to self-repair is an inherent and natural characteristic of all life forms on earth. As opposed to nature, man-made systems are in most cases not inherently robust and a…

Neural and Evolutionary Computing · Computer Science 2016-11-15 Christof Teuscher

An object-oriented combinator chemistry was used to construct an artificial organism with a system architecture possessing characteristics necessary for organisms to evolve into more complex forms. This architecture supports modularity by…

Neural and Evolutionary Computing · Computer Science 2018-05-17 Lance R. Williams

Biology is perhaps the most complex of the sciences, given the incredible variety of chemical species that are interconnected in spatial and temporal pathways that are daunting to understand. Their interconnections lead to emergent…

Biological Physics · Physics 2023-09-11 Henry V. Jakubowski , Henry Agnew , Bartholomew E. Jardine , Herbert M. Sauro

We study directed random graphs (random graphs whose edges are directed) as they evolve in discrete time by the addition of nodes and edges. For two distinct evolution strategies, one that forces the graph to a condition of near acyclicity…

Statistical Mechanics · Physics 2007-05-23 Valmir C. Barbosa , Raul Donangelo , Sergio R. Souza

Under suitable assumptions, the dynamic behaviour of a chemical reaction network is governed by an autonomous set of polynomial ordinary differential equations over continuous variables representing the concentrations of the reactant…

Dynamical Systems · Mathematics 2014-07-15 Matthew D. Johnston , David Siegel

A directed hypergraph, which consists of nodes and hyperarcs, is a higher-order data structure that naturally models directional group interactions (e.g., chemical reactions of molecules). Although there have been extensive studies on local…

Data Structures and Algorithms · Computer Science 2023-11-27 Heechan Moon , Hyunju Kim , Sunwoo Kim , Kijung Shin

"Composable Life" is a hybrid project blending design fiction, experiential virtual reality, and scientific research. Through a multi-perspective, cross-media approach to speculative design, it reshapes our understanding of the digital…

Computers and Society · Computer Science 2025-08-29 Botao Amber Hu , Fangting

A recent article by Weidner et al. [2021] presents a method to extract graph properties that are predictive of the dynamical behavior of multivariate, discrete models of biochemical regulation. In other words, a method that uses only…

Quantitative Methods · Quantitative Biology 2021-10-22 Luis M. Rocha

It is fundamental for science and technology to be able to predict chemical reactions and their properties. To achieve such skills, it is important to develop good representations of chemical reactions, or good deep learning architectures…

Machine Learning · Computer Science 2022-01-05 Mohammadamin Tavakoli , Alexander Shmakov , Francesco Ceccarelli , Pierre Baldi
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