Uncover the latest and most impactful research in Evolvability. Explore pioneering discoveries, insightful ideas and new methods from leading researchers in the field.
This paper introduces a reliability model for a two-unit degradable computing architecture that includes a coverage factor within its redundant configuration. A primary challenge in modelling such real-world systems is that key parameters failure...
Learning robust and discriminative representations from gastrointestinal endoscopy images remains challenging due to high visual variability, subtle pathological differences, and pronounced class imbalance. While variational autoencoders (VAEs) have...
Dozens of independent origins of multicellularity have profoundly shaped Earth’s evolutionary and ecological history. These transitions have given rise to massive radiations encompassing thousands to millions of species and the evolution of...
Antibiotic resistance has emerged as a major bottleneck in antibiotic development, frequently undermining promising drug candidates and negating years of research and pharmaceutical investment. Despite growing recognition of this issue, discovery...
Multi-objective multi-task optimization (MO-MTO), which aims to simultaneously solve multiple related multi-objective problems by leveraging knowledge transfer across tasks to enhance optimization performance on each task, has emerged as a new...
Evolutionary multitask optimization (EMTO) seeks to solve multiple optimization problems simultaneously by exploiting latent relationships between tasks. Among existing EMTO approaches, the Multifactorial Evolutionary Algorithm (MFEA) has shown...
Selecting a committee of size k from a set of candidates involves a delicate balance between maximizing individual excellence and ensuring group compatibility. Recent literature has proposed the k-Shapley value-based committee rule (Dutta et al. 2024...
Technological evolution analysis is critical to identify technology opportunities and develop innovation strategy. Existing approaches represent patents as keywords, topics or syntactic triples, overlooking the causality of the inventive process....
This paper introduces a reconfigurable structural mechanism for unmanned aerial vehicles that transforms the same mechanical elements from propeller shields into adaptive landing legs. The concept is developed for drones operating in built cultural...
Automatic test data generation constitutes a fundamental pillar of software quality assurance, playing an instrumental role in both defect detection and the reduction of development lifecycle costs. Within this domain, Search-Based Software Testing...
The structural integrity and electrical reliability of wearable electronics heavily depend on the physical properties of the underlying substrate. While previous research established a theoretical framework for modeling electrical degradation in...
Combinatorial optimization (CO) underpins decision-making across science, engineering and industry, especially manufacturing, logistics, healthcare operations and energy management. However, designing effective heuristics for each new problem...
NeuroEvolution is scalable alternative for gradient-based deep reinforcement learning, which provides parallel, gradient-free optimization that overcomes backpropagation’s limitations. However, the selection of the neural network activation function...
This article introduces organismic agency as the principle of individual selection.Individual selection involves the organism itself selecting a behavior or development according to individual preference metrics. It is the explanatory counterpart...
In recent decades, numerous notable meta-heuristic algorithms have been developed to tackle complex optimization problems. Nevertheless, these existing meta-heuristics need to be enhanced with various evolutionary techniques to tackle new challenges...
Humanoid locomotion over varying terrains typically relies on exteroceptive perception or manually tuned control gains, both of which limit robustness in real-world deployment. This paper presents a fully proprioceptive terrain-adaptive control...
Despite evolution by natural selection being a deterministic process well-established across both science and society, the extent to which evolution can be predicted remains debated. A large body of previous work has usefully highlighted how...
The paper Markov constraints: steerable generation of Markov sequencesstarted from a practical problem in interactive music generation: Markov models are effective at reproducing local style, but are poor at obeying non-local user intentions. Our...
This paper proposes a new population-based metaheuristic, termed Platypus Electroreception Optimization (PEO), inspired by the multimodal foraging behavior of the platypus (Ornithorhynchus anatinus). The algorithm integrates three search components:...
The journal of Genetic Programming and Evolvable Machinesis devoted to reporting innovative and significant progress in automatic evolution of...
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What we publish Biology & Philosophyaims to publish the best original work in philosophy of biology, broadly understood to span conceptual,...
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Many instances of research in computer science and artificial intelligence (AI) draw inspiration from metaphorical real-world physical and biological...
