AI & Machine Learning · Computer Science & AI
Neural & Evolutionary Computing
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324 papers, from 4 September 2026 to 5 November 2026: 324 arXiv preprints.
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Newest papers, page 14
Self-Replicating Neural Cellular Automata: Quantifying Emergent Phenotypic and Genotypic Diversity in an OpenEnded Substrate
We study an in-silico substrate in which every pixel of a two-channel cellular-automata grid carries a tiny neural network (an agent) that senses its Moore neighborhood.Position Paper: Neurotransmitters as a Missing Dimension in Artificial Neural Networks
Artificial neural networks (ANNs), as core components of modern deep learning (DL) systems, lack the adaptive flexibility and long-term stability exhibited by biological systems.Neural noise enables accurate internal simulation of rare events
The brain needs an accurate internal model of the world to generate predictions and guide behavior.Benchmarking Tabular Foundation Models as Surrogates in Expensive Evolutionary Optimization
Surrogate-assisted evolutionary algorithms (SAEAs) are effective methods for solving expensive optimization problems (EOPs), where surrogate models replace most expensive evaluations and critically…Transformation Laws in Neural Representations: Structure, Realisability, and Construction
How neural representations preserve the structure of input changes connects representation analysis with internal intervention.The evolution of sex for artificial intelligence: a population-genetic framework for multigenerational model populations
Some aspects of AI development resemble a population process in which models are specialised, retrained on the output of peers, or combined by averaging weights.ReDIL-GNN: Resynthesis Domain Incremental Learning for Circuit Graph Neural Networks
Logic resynthesis preserves circuit functionality while changing gate vocabulary, topology, and structural statistics, creating domain shift for circuit graph neural networks (GNNs) without changing…A Metaheuristic Optimization Framework for Discrete Optimization under Strict Time Limits
Real-time applications often rely on optimization approaches that can find high-quality solutions to hard problems on the order of milliseconds.Artificial Neural Networks as Surrogate Models in Black Box Optimization
Black-Box Optimization (BBO) is often applied in several engineering fields and can utilize an advancement of numerical measure- ments and simulation technologies.Learning to Optimize UAV Path Planning for Data Sensing in Wireless Sensor Networks
UAVs have emerged as highly flexible platforms for data sensing in Wireless Sensor Networks (WSNs).Geometry of learning dynamics: Gradient descent versus natural gradient on the ridge of optimization
High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit a "Ridge of Optimization" characterized by extreme stability and a highly skewed weight spectrum.Information Geometric Self-Organization at the Edge of Stability in High-Capacity Kernel Associative Memories
High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit exceptional storage capabilities and robustness.LLMDE: A Large Language Model-Driven Differential Evolution Algorithm for Portfolio Optimization
This study proposes a Large Language Model-Driven Differential Evolution (LLMDE) algorithm to reduce the reliance on handcrafted hyperparameter design.Neuro-Symbolic Hierarchical Intention Anticipation in Human Behavior
Assistive autonomous systems must anticipate human goals before an observed behavior is complete.Bio-Inspired Palette Evolution in Indirectly Encoded Substrates: Timescale Compatibility Shapes Activation Function Discovery
Indirectly encoded neural networks can assign different activation functions to individual nodes, but the right functions are rarely known in advance.Event-based Selective Attention for Multi-resolution Fast Region of Interest (ROI) Detection
Neuromorphic vision systems operate under strict constraints on bandwidth, memory, and energy, particularly at the edge, motivating early mechanisms for data reduction and selective processing.Machine Zygote: Causal Biparental Heredity Before Learning in a Germline--Soma Artificial Agent
Artificial ontogeny, developmental encodings, robot reproduction, and inherited controllers are established research directions, yet a narrower question remains: can a newborn artificial agent…A Spatiotemporal Extension of the Neuromorphic DBSCAN Implementation
DBSCAN is an algorithm that denoises and clusters data.Graph neural networks for exoplanet atmospheres
Calculating disequilibrium chemistry in exoplanet atmospheres remains a significant computational bottleneck in atmospheric retrievals.Sensory Precision Inference for Multimodal Arbitration under Uncertainty
Autonomous agents operating on multisensory data cannot assume that all sensory modalities remain consistently informative.