23 papers · ranked by Valyu relevance
Dario Floreano, Laurent Keller
The first proposal that Darwinian selection could generate efficient control systems can be attributed to Alan Turing in the 1950s. He suggested that intelligent machines capable of adaptation and learning would be too difficult to conceive by a human designer and could instead be obtained by using an evolutionary…
Nicolas Bredeche, Evert Haasdijk, Abraham Prieto
This article provides an overview of evolutionary robotics techniques applied to online distributed evolution for robot collectives, namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. This article also presents a…
Reem Alattas, Sarosh Patel, Tarek Sobh
Reem J. Alattas is a Ph.D. candidate majoring in Computer Science and Engineering at the University of Bridgeport. She received her B.Sc. and M.Sc. in Computer Science from King Saud University. Reem is a member of several professional organizations including; IEEE, SWE, Phi Kappa Phi, and PMI. Her current research…
Evert Haasdijk, Nicolas Bredeche, A. E. Eiben, Eleni Vasilaki
Embodied evolutionary robotics is a sub-field of evolutionary robotics that employs evolutionary algorithms on the robotic hardware itself, during the operational period, i.e., in an on-line fashion. This enables robotic systems that continuously adapt, and are therefore capable of (re-)adjusting themselves to…
Ágoston E. Eiben, Jacintha Ellers, Gerben Meynen, Sven Nyholm
Rapid developments in evolutionary computation, robotics, 3D-printing, and material science are enabling advanced systems of robots that can autonomously reproduce and evolve. The emerging technology of robot evolution challenges existing AI ethics because the inherent adaptivity, stochasticity, and complexity of…
Nicolas Bredèche, Evert Haasdijk, Abraham Prieto
This paper provides an overview of evolutionary robotics techniques applied to on-line distributed evolution for robot collectives – namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. The paper also presents a…
Hari Mohan Pandey
This paper reviews various Evolutionary Approaches applied to the domain of Evolutionary Robotics with the intention of resolving difficult problems in the areas of robotic design and control. Evolutionary Robotics is a fast-growing field that has attracted substantial research attention in recent years. The paper thus…
David Howard
This commentary follows on from a recently-published guest editorial in Frontiers in Robotics and AI entitled Evolving Robotic Morphologies (). Motivated by findings from the many quality submissions, the central thesis of this contribution is that evolutionary robotics and field robotics, despite seeming rather…
Alan F. T. Winfield
The use of evolutionary robotic systems to model aspects of evolutionary biology is well-established. Yet, few studies have asked the question, “What kind of model is an evolutionary robotic system?” This paper seeks to address that question in several ways. First, it is addressed by applying a structured model…
Tønnes F. Nygaard, Charles Martín, Eivind Samuelsen, Jim Tørresen + 1 more
'Kyrre Glette'] For robots to handle the numerous factors that can affect them in the real world, they must adapt to changes and unexpected events. Evolutionary robotics tries to solve some of these issues by automatically optimizing a robot for a specific environment. Most of the research in this field, however, uses…
Matteo De Carlo, Eliseo Ferrante, Daan Zeeuwe, Jacintha Ellers + 2 more
'Gerben Meynen' 'A. E. Eiben'] Abstract—In the field of evolutionary robotics, choosing the correct encoding is very complicated, especially when robots evolve both behaviours and morphologies at the same time. With the objective of improving our understanding of the mapping process from encodings to functional robots…
Jie Luo
—Evolutionary robotics offers a powerful framework for designing and evolving robot morphologies, particularly in the context of modular robots. However, the role of query mechanisms during the genotype-to-phenotype mapping process has been largely overlooked. This research addresses this gap by conducting a…
Renata B. Biazzi, André Fujita, Daniel Y. Takahashi
Active, directed locomotion on the ground is present in many phylogenetically distant species. Bilateral symmetry and modularity of the body are common traits often associated with improved directed locomotion. Nevertheless, both features result from natural selection, which is contingent (history-dependent) and…
Stefano Nolfi, Paolo Pagliuca
We investigate the use of competitive co-evolution for synthesizing progressively better solutions. Specifically, we introduce a set of methods to measure historical and global progress. We discuss the factors that facilitate genuine progress. Finally, we compare the efficacy of four qualitatively different algorithms.…
Arthur Bernard, Nicolas Bredeche, Jean-Baptiste André
Evolutionary game theory shows that social interactions involving coordination between individuals are subject to an “evolutionary trap.” Once a suboptimal strategy has evolved, mutants playing an alternative strategy are counterselected because they fail to coordinate with the majority. This creates a detrimental…
Ryusuke Fujisawa, Genki Ichinose, Shigeto Dobata
The evolution of complexity is one of the prime features of life on Earth. Although well accepted as the product of adaptation, the dynamics underlying the evolutionary build-up of complex adaptive systems remains poorly resolved. Using simulated robot swarms that exhibit ant-like group foraging with trail pheromones…
Ruyun Hu, Lihao Fu, Yongcan Chen, Junyu Chen + 2 more
Protein engineering aims to find top functional sequences in a vast design space. For such an expensive “black-box” function optimization problem, Bayesian optimization is a principled sample-efficient approach, which is guided by a surrogate model of the objective function. Unfortunately, Bayesian optimization is…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Kyle Harrington, Jordan Pollack
The escalation of complexity is a commonly cited benefit of coevolutionary systems, but computational simulations generally fail to demonstrate this capacity to a satisfactory degree. We draw on a macroevolutionary theory of escalation to develop a set of criteria for coevolutionary systems to exhibit escalation of…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
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Despite the promise of self-driving laboratories to accelerate discovery, their widespread implementation is hindered by prohibitive cost and technical complexity. We introduce BrickSDLab, a fully functional self-driving lab platform built entirely from LEGO® components, designed to bridge this accessibility gap.…
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Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a…
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Organic molecular crystals offer a broad spectrum of potential applications. The vast number of possible molecules is both an opportunity and a challenge, because of the prohibitive expense of exhaustively searching chemical space to find novel molecules with promising solid-state properties. Computational methods can…