18 papers · ranked by Valyu relevance
Carlos Contreras Bolton, Gustavo Gatica, Víctor Parada, Aaron Alain-Jon Golden
'Aaron Alain-Jon Golden'] The vertex coloring problem is a classical problem in combinatorial optimization that consists of assigning a color to each vertex of a graph such that no adjacent vertices share the same color, minimizing the number of colors used. Despite the various practical applications that exist for…
Santiago Hernández-Orozco, Narsis A. Kiani, Hector Zenil
Natural selection explains how life has evolved over millions of years from more primitive forms. The speed at which this happens, however, has sometimes defied formal explanations when based on random (uniformly distributed) mutations. Here, we investigate the application of a simplicity bias based on a natural but…
Licheng Jiao, Jiaxuan Zhao, Chao Wang, Xu Liu + 6 more
'Lingling Li' 'Ronghua Shang' 'Yangyang Li' 'Wenping Ma' 'Shuyuan Yang'] Nature, with its numerous surprising rules, serves as a rich source of creativity for the development of artificial intelligence, inspiring researchers to create several nature-inspired intelligent computing paradigms based on natural mechanisms.…
Bill O'Neill
In silico experiments reveal how evolution can work--without missing links. What can biologists learn from them?
Sizhe Yuen, Thomas H. G. Ezard, Adam J. Sobey
Evolutionary computation is a group of biologically inspired algorithms used to solve complex optimization problems. It can be split into evolutionary algorithms, which take inspiration from genetic inheritance, and swarm intelligence algorithms, that take inspiration from cultural inheritance. However, much of the…
Rosangela Canino-Koning, Michael J. Wiser, Charles Ofria, Laurent Keller
'Laurent Keller'] Genetic spaces are often described in terms of fitness landscapes or genotype-to-phenotype maps, where each genetic sequence is associated with phenotypic properties and linked to other genotypes that are a single mutational step away. The positions close to a genotype make up its “mutational…
Alexander V. Spirov, Ekaterina M. Myasnikova, Josh Bongard
Evolutionary computing (EC) is an area of computer sciences and applied mathematics covering heuristic optimization algorithms inspired by evolution in Nature. EC extensively study all the variety of methods which were originally based on the principles of selectionism. As a result, many new algorithms and approaches…
Innocent Sibanda, Geoff Nitschke
The goal of bioengineering in synthetic biology is to redesign, reprogram, and rewire biological systems for specific applications using standardized parts such as promoters and ribosomes. For example, bioengineered micro-organisms capable of cleaning up environmental pollution or producing antibodies de novo to defend…
Chrisantha Fernando, Vera Vasas, Eörs Szathmáry, Phil Husbands + 1 more
'Gonzalo G. de Polavieja'] We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model.…
Diego Navarro-Mateu, Ana Cocho-Bermejo
The majority of current visual-algorithmic architecture is constricted to specific parameters that are gradient related, keeping their parts’ relation fixed within the algorithm, far away from a truly parametric modeling with a flexible topology. Recent findings around genetics and certain genes capable of shape…
Oliver Attie, Brian Sulkow, Chong Di, Weigang Qiu + 1 more
The Standard Genetic Code (SGC) is robust to mutational errors such that frequently occurring mutations minimally alter the physio-chemistry of amino acids. The apparent correlation between the evolutionary distances among codons and the physio-chemical distances among their cognate amino acids suggests an early…
Laura M. Grabowski, David M. Bryson, Fred C. Dyer, Robert T. Pennock + 2 more
'Charles Ofria' 'Paul Graham'] Investigating the evolution of animal behavior is difficult. The fossil record leaves few clues that would allow us to recapitulate the path that evolution took to build a complex behavior, and the large population sizes and long time scales required prevent us from re-evolving such…
Alexander O. Gusev, Leonid M. Martyushev, Robert Niven, Hisashi Ozawa
'Hisashi Ozawa'] The simplest evolutionary model for catching prey by an agent (predator) is considered. The simulation is performed on the basis of a software-emulated Intel i8080 processor. Maximizing the number of catches is chosen as the objective function. This function is associated with energy dissipation and…
Steven A. Frank, Antonio M. Scarfone
Diverse learning algorithms, optimization methods, and natural selection share a common mathematical structure despite their apparent differences. Here, I show that a simple notational partitioning of change by the Price equation reveals a universal force-metric-bias (FMB) law: $Δθ=(Mf+b+ξ)$. The force $f$ drives…
Simeon D. Castle, Michiel Stock, Thomas E. Gorochowski
Careful consideration of how we approach design is crucial to all areas of biotechnology. However, choosing or developing an effective design methodology is not always easy as biology, unlike most areas of engineering, is able to adapt and evolve. Here, we put forward that design and evolution follow a similar cyclic…
Michael Tetteh, Douglas Mota Dias, Conor Ryan
The evolution of complex circuits remains a challenge for the Evolvable Hardware field in spite much effort. There are two major issues: the amount of testing required and the low evolvability of representation structures to handle complex circuitry, at least partially due to the destructive effects of genetic…
Troy Day
The process of evolutionary diversification unfolds in a vast genotypic space of potential outcomes. During the past century, there have been remarkable advances in the development of theory for this diversification, and the theory's success rests, in part, on the scope of its applicability. A great deal of this theory…
András Szilágyi, István Zachar, Anna Fedor, Harold P. de Vladar + 1 more
'Eörs Szathmáry'] Background: The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian…