:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Rentschler, Micah, Roberts, Jesse
Formato:	Preprint
Publicado:	2026
Materias:	Neural and Evolutionary Computing
Acceso en línea:	https://arxiv.org/abs/2601.21268
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents
por: Pigozzi, Federico, et al.
Publicado: (2026)

Meta-Learning an Evolvable Developmental Encoding
por: Montero, Milton L., et al.
Publicado: (2024)

Spiking World Model with Multi-Compartment Neurons for Model-based Reinforcement Learning
por: Sun, Yinqian, et al.
Publicado: (2025)

Large Language Model Assisted Automated Algorithm Generation and Evolution via Meta-black-box optimization
por: Yang, Xu, et al.
Publicado: (2025)

Evolving Reservoirs for Meta Reinforcement Learning
por: Léger, Corentin, et al.
Publicado: (2023)

Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals
por: Sijben, E. M. C., et al.
Publicado: (2024)

Exploring the True Potential: Evaluating the Black-box Optimization Capability of Large Language Models
por: Huang, Beichen, et al.
Publicado: (2024)

Brain-inspired Computational Modeling of Action Recognition with Recurrent Spiking Neural Networks Equipped with Reinforcement Delay Learning
por: Nadafian, Alireza, et al.
Publicado: (2024)

Evolutionary Reinforcement Learning: A Systematic Review and Future Directions
por: Lin, Yuanguo, et al.
Publicado: (2024)

Deep Reinforcement Learning-Assisted Component Auto-Configuration of Differential Evolution Algorithm for Constrained Optimization: A Foundation Model
por: Yang, Xu, et al.
Publicado: (2025)

Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning
por: Raymond, Christian, et al.
Publicado: (2022)

EvoRL: A GPU-accelerated Framework for Evolutionary Reinforcement Learning
por: Zheng, Bowen, et al.
Publicado: (2025)

Evolutionary Reinforcement Learning for Interpretable Decision-Making in Supply Chain Management
por: Genetti, Stefano, et al.
Publicado: (2025)

Human-in-the-Loop Policy Optimization for Preference-Based Multi-Objective Reinforcement Learning
por: Li, Ke, et al.
Publicado: (2024)

Collaborative Ground-Space Communications via Evolutionary Multi-objective Deep Reinforcement Learning
por: Li, Jiahui, et al.
Publicado: (2024)

Lexidate: Model Evaluation and Selection with Lexicase
por: Hernandez, Jose Guadalupe, et al.
Publicado: (2024)

Deep Reinforcement Learning-Assisted Automated Operator Portfolio for Constrained Multi-objective Optimization
por: Shao, Shuai, et al.
Publicado: (2026)

CaRe-BN: Precise Moving Statistics for Stabilizing Spiking Neural Networks in Reinforcement Learning
por: Xu, Zijie, et al.
Publicado: (2025)

Optimizing Interplanetary Trajectories using Hybrid Meta-heuristic
por: Dehkordi, Amin Abdollahi, et al.
Publicado: (2025)

A Unified Platform to Evaluate STDP Learning Rule and Synapse Model using Pattern Recognition in a Spiking Neural Network
por: Maskeen, Jaskirat Singh, et al.
Publicado: (2025)

Large Language Models as Evolutionary Optimizers
por: Liu, Shengcai, et al.
Publicado: (2023)

Solving Expensive Optimization Problems in Dynamic Environments with Meta-learning
por: Zhang, Huan, et al.
Publicado: (2023)

Equilibrium Propagation Without Limits
por: Litman, Elon
Publicado: (2025)

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning
por: Wang, Boxiong, et al.
Publicado: (2025)

Aerial Reliable Collaborative Communications for Terrestrial Mobile Users via Evolutionary Multi-Objective Deep Reinforcement Learning
por: Sun, Geng, et al.
Publicado: (2025)

Adaptive Spiking Neurons for Vision and Language Modeling
por: Zhou, Chenlin, et al.
Publicado: (2026)

When Large Language Model Meets Optimization
por: Huang, Sen, et al.
Publicado: (2024)

Exploring Extreme Quantization in Spiking Language Models
por: Bal, Malyaban, et al.
Publicado: (2024)

Large Language Models as Particle Swarm Optimizers
por: Shinohara, Yamato, et al.
Publicado: (2025)

Large Language Models as Surrogate Models in Evolutionary Algorithms: A Preliminary Study
por: Hao, Hao, et al.
Publicado: (2024)

Winner-Take-All Spiking Transformer for Language Modeling
por: Zhou, Chenlin, et al.
Publicado: (2026)

Increasing Computation Resolves Conflicts in Vision Language Models
por: Wang, Bingyang, et al.
Publicado: (2025)

Reproducing and Dissecting Denoising Language Models for Speech Recognition
por: Koch, Dorian, et al.
Publicado: (2025)

Neuromorphic Reinforcement Learning for Quadruped Locomotion Control on Uneven Terrain
por: Han, Zhuangyu, et al.
Publicado: (2026)

Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing
por: Humeniuk, Dmytro, et al.
Publicado: (2023)

ORS: A novel Olive Ridley Survival inspired Meta-heuristic Optimization Algorithm
por: Panigrahi, Niranjan, et al.
Publicado: (2024)

Automatic Design of Optimization Test Problems with Large Language Models
por: Achtelik, Wojciech, et al.
Publicado: (2026)

Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms
por: Yin, Haoran, et al.
Publicado: (2024)

Explaining Genetic Programming Trees using Large Language Models
por: Maddigan, Paula, et al.
Publicado: (2024)

Language Model Crossover: Variation through Few-Shot Prompting
por: Meyerson, Elliot, et al.
Publicado: (2023)