Copertina

Evolutionary System 2 Reasoning: An Empirical Proof

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ma, Zeyuan, Huang, Wenqi, Song, Guo-Huan, Guo, Hongshu, Ma, Sijie, Cao, Zhiguang, Gong, Yue-Jiao
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

RLEMMO: Evolutionary Multimodal Optimization Assisted By Deep Reinforcement Learning
di: Lian, Hongqiao, et al.
Pubblicazione: (2024)

Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning
di: Ma, Zeyuan, et al.
Pubblicazione: (2024)

Deep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution
di: Guo, Hongshu, et al.
Pubblicazione: (2024)

A Novel Two-Phase Cooperative Co-evolution Framework for Large-Scale Global Optimization with Complex Overlapping
di: Qiu, Wenjie, et al.
Pubblicazione: (2025)

LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation
di: Ma, Zeyuan, et al.
Pubblicazione: (2024)

Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineering
di: Wang, Chen, et al.
Pubblicazione: (2025)

READY: Reward Discovery for Meta-Black-Box Optimization
di: Huang, Zechuan, et al.
Pubblicazione: (2026)

ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning
di: Guo, Hongshu, et al.
Pubblicazione: (2024)

Meta-Black-Box-Optimization through Offline Q-function Learning
di: Ma, Zeyuan, et al.
Pubblicazione: (2025)

Architectural Scaling Surpass Basis Complexity? Efficient KANs with Single-Parameter Design
di: Chen, Zhijie, et al.
Pubblicazione: (2024)

Reinforcement Learning-assisted Constraint Relaxation for Constrained Expensive Optimization
di: Zhu, Qianhao, et al.
Pubblicazione: (2026)

MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization
di: Ma, Zeyuan, et al.
Pubblicazione: (2025)

Offline Multi-Task Multi-Objective Data-Driven Evolutionary Algorithm with Language Surrogate Model and Implicit Q-Learning
di: Zhang, Xian-Rong, et al.
Pubblicazione: (2025)

Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
di: Li, Qi, et al.
Pubblicazione: (2025)

Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization
di: Ma, Zeyuan, et al.
Pubblicazione: (2024)

Reinforcement Learning-based Self-adaptive Differential Evolution through Automated Landscape Feature Learning
di: Guo, Hongshu, et al.
Pubblicazione: (2025)

COBRA++: Enhanced COBRA Optimizer with Augmented Surrogate Pool and Reinforced Surrogate Selection
di: Yu, Zipei, et al.
Pubblicazione: (2026)

Surrogate Ensemble in Expensive Multi-Objective Optimization via Deep Q-Learning
di: Wu, Yuxin, et al.
Pubblicazione: (2026)

GeM-EA: A Generative and Meta-learning Enhanced Evolutionary Algorithm for Streaming Data-Driven Optimization
di: Wu, Yue, et al.
Pubblicazione: (2026)

Detect and Act: Automated Dynamic Optimizer through Meta-Black-Box Optimization
di: Gao, Zijian, et al.
Pubblicazione: (2026)

A Learning-Based Cooperative Coevolution Framework for Heterogeneous Large-Scale Global Optimization
di: Qiu, Wenjie, et al.
Pubblicazione: (2026)

Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
di: Chen, Jiacheng, et al.
Pubblicazione: (2024)

Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization
di: Ma, Zeyuan, et al.
Pubblicazione: (2024)

RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
di: Yi, Hang, et al.
Pubblicazione: (2026)

Effective Learning for Small Reasoning Models: An Empirical Study on 0.5B Reasoning LLMs
di: Zhuang, Xialie, et al.
Pubblicazione: (2025)

DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization
di: Guo, Hongshu, et al.
Pubblicazione: (2025)

Advancing CMA-ES with Learning-Based Cooperative Coevolution for Scalable Optimization
di: Guo, Hongshu, et al.
Pubblicazione: (2025)

Surrogate Learning in Meta-Black-Box Optimization: A Preliminary Study
di: Ma, Zeyuan, et al.
Pubblicazione: (2025)

Evolution of Benchmark: Black-Box Optimization Benchmark Design through Large Language Model
di: Wang, Chen, et al.
Pubblicazione: (2026)

Evolutionary Neural Architecture Search with Dual Contrastive Learning
di: Zhang, Xian-Rong, et al.
Pubblicazione: (2025)

Hybrid-Balance GFlowNet for Solving Vehicle Routing Problems
di: Zhang, Ni, et al.
Pubblicazione: (2025)

Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models
di: Liu, Yongjiang, et al.
Pubblicazione: (2025)

MEME: Modeling the Evolutionary Modes of Financial Markets
di: Guo, Taian, et al.
Pubblicazione: (2026)

Probing Neural Combinatorial Optimization Models
di: Zhang, Zhiqin, et al.
Pubblicazione: (2025)

Evaluating Frontier LLMs on PhD-Level Mathematical Reasoning: A Benchmark on a Textbook in Theoretical Computer Science about Randomized Algorithms
di: Cao, Yang, et al.
Pubblicazione: (2025)

Large Language Model as Meta-Surrogate for Data-Driven Many-Task Optimization: A Proof-of-Principle Study
di: Zhang, Xian-Rong, et al.
Pubblicazione: (2025)

Learning to Handle Complex Constraints for Vehicle Routing Problems
di: Bi, Jieyi, et al.
Pubblicazione: (2024)

MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
di: Zhou, Jianan, et al.
Pubblicazione: (2024)

An Empirical Study of Reasoning Steps in Thinking Code LLMs
di: Xue, Haoran, et al.
Pubblicazione: (2025)

RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States
di: Xiao, Xiangjie, et al.
Pubblicazione: (2026)