Results 81 to 90 of about 2,128 (206)
Cultural enhancement of neuroevolution [PDF]
, 2002 textAny transmission of behavior from one generation to the next via non–genetic means is a process of culture. Culture provides major advantages for survival in the biological world.
McQuesten, Paul Herbert
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Transforming Grain‐Boundary Brittle Precipitates to Ductility Pathways in Complex Concentrated Alloy
Advanced Science, Volume 13, Issue 19, 2 April 2026.By engineering graded BCC/L12 interfaces, brittle precipitates in a complex concentrated alloy enable sequential deformation, realizing gigapascal strength with >20% elongation to solve the strength‐ductility trade‐off. ABSTRACT Conventional wisdom holds that hard grain‐boundary (GB) precipitates embrittle structural alloys by acting as crack ...
Zhixin Li +14 more
wiley +1 more source
Materials Genome Engineering Advances, Volume 4, Issue 1, March 2026.We develop an efficient GPU implementation of the hybrid Monte Carlo and molecular dynamics method in the GPUMD package and use it, in combination with the neuroevolution potential, to simulate the segregation of 15 solutes in polycrystalline Al, revealing distinct segregation patterns and the mechanisms of solute strengthening and embrittlement ...
Keke Song +6 more
wiley +1 more source
Neuroevolution-Based Network Architecture Evolution in Semiconductor Manufacturing
Promoted model architectures or algorithms are crucial for intelligent manufacturing since developing them takes a lot of trial and error to embed the domain knowledge into the models correctly.
Bing-Ru Jiang (16698963) +2 more
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Numerical optimization with neuroevolution
, 2002 - Neuroevolution techniques have been successful in many sequential decision tasks such as robot control and game playing. This paper aims at establishing whether they can be useful in numerical optimization more generally, by comparing neuroevolution to
Brian Greer, Risto Lahdelma
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Review of some contemporary trends in machine learning technology
E-Management, 2019 The construction of machine learning systems constitutes today one of the most popular, relevant and modern areas of human activity at the interface of information technology, mathematical analysis and statistics.
M. Koroteev
doaj +1 more source
Particle Swarm Optimization and Random Search for Convolutional Neural Architecture Search
IEEE AccessEvolutionary and swarm intelligence-based algorithms are commonly used as the search strategy component in Neural Architecture Search (NAS). However, little work has been done to quantify the performance improvements that these nature-inspired ...
Kosmas Deligkaris
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On the Preservation of Input/Output Directed Graph Informativeness Under Crossover
Complexity, Volume 2026, Issue 1, 2026.There exists a broad class of networks that connect inputs to outputs. These networks include chemical transformation networks, electrical circuits, municipal water systems, and neural networks. The goals of this paper are to provide a theoretical foundation for evolutionary crossover on this class of graphs and connect crossover to informativeness, a ...
Andreas Duus Pape +4 more
wiley +1 more source
Evolving a Dynamic Predictive Coding Mechanism for Novelty Detection [PDF]
, 2007 Novelty detection is a machine learning technique which identifies new or unknown information in data sets. We present three evolutionary algorithms, a simple genetic algorithm, NEAT and FS-NEAT, for the the task of optimising the structure of an ...
Haggett, Simon J. +3 more
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Generative NeuroEvolution for Deep Learning
CoRR, 2013 An important goal for the machine learning (ML) community is to create approaches that can learn solutions with human-level capability. One domain where humans have held a significant advantage is visual processing. A significant approach to addressing this gap has been machine learning approaches that are inspired from the natural systems, such as ...
Phillip Verbancsics, Josh Harguess
openaire +3 more sources