Cover Image

Dual-Agent Reinforcement Learning for Automated Feature Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gao, Wanfu, Man, Zengyao, Pan, Hanlin, Liu, Kunpeng
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Two-Stage Feature Generation with Transformer and Reinforcement Learning
by: Gao, Wanfu, et al.
Published: (2025)

Reconsidering Feature Structure Information and Latent Space Alignment in Partial Multi-label Feature Selection
by: Pan, Hanlin, et al.
Published: (2025)

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning
by: Gao, Wanfu, et al.
Published: (2025)

Graph Random Walk with Feature-Label Space Alignment: A Multi-Label Feature Selection Method
by: Gao, Wanfu, et al.
Published: (2025)

Uncertainty-Aware Global-View Reconstruction for Multi-View Multi-Label Feature Selection
by: Hao, Pingting, et al.
Published: (2025)

From Ambiguity to Action: A POMDP Perspective on Partial Multi-Label Ambiguity and Its Horizon-One Resolution
by: Pan, Hanlin, et al.
Published: (2026)

TFWT: Tabular Feature Weighting with Transformer
by: Zhang, Xinhao, et al.
Published: (2024)

Redundancy-optimized Multi-head Attention Networks for Multi-View Multi-Label Feature Selection
by: Liu, Yuzhou, et al.
Published: (2025)

Ca-MCF: Category-level Multi-label Causal Feature selection
by: Gao, Wanfu, et al.
Published: (2026)

Heterogeneous Multi-Agent Reinforcement Learning with Attention for Cooperative and Scalable Feature Transformation
by: Zhe, Tao, et al.
Published: (2025)

SEHFS: Structural Entropy-Guided High-Order Correlation Learning for Multi-View Multi-Label Feature Selection
by: Peng, Cheng, et al.
Published: (2026)

Feature Interaction Aware Automated Data Representation Transformation
by: Azim, Ehtesamul, et al.
Published: (2023)

The Semantic Architect: How FEAML Bridges Structured Data and LLMs for Multi-Label Tasks
by: Gao, Wanfu, et al.
Published: (2025)

Topology-aware Reinforcement Feature Space Reconstruction for Graph Data
by: Ying, Wangyang, et al.
Published: (2024)

$Agent^2$: An Agent-Generates-Agent Framework for Reinforcement Learning Automation
by: Wei, Yuan, et al.
Published: (2025)

Causally-Guided Automated Feature Engineering with Multi-Agent Reinforcement Learning
by: Malarkkan, Arun Vignesh, et al.
Published: (2026)

Automation and Feature Selection Enhancement with Reinforcement Learning (RL)
by: Nagaraju, Sumana Sanyasipura
Published: (2025)

DRTA: Dynamic Reward Scaling for Reinforcement Learning in Time Series Anomaly Detection
by: Golchin, Bahareh, et al.
Published: (2025)

Collaborative Multi-Agent Reinforcement Learning for Automated Feature Transformation with Graph-Driven Path Optimization
by: Huang, Xiaohan, et al.
Published: (2025)

Dynamic and Adaptive Feature Generation with LLM
by: Zhang, Xinhao, et al.
Published: (2024)

On Representation Complexity of Model-based and Model-free Reinforcement Learning
by: Zhu, Hanlin, et al.
Published: (2023)

A Dual-Agent Adversarial Framework for Robust Generalization in Deep Reinforcement Learning
by: Xie, Zhengpeng, et al.
Published: (2025)

Automated Feature Selection for Inverse Reinforcement Learning
by: Baimukashev, Daulet, et al.
Published: (2024)

An Evolving Scenario Generation Method based on Dual-modal Driver Model Trained by Multi-Agent Reinforcement Learning
by: Wu, Xinzheng, et al.
Published: (2025)

Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning
by: Hsu, Hao-Lun, et al.
Published: (2024)

Learned Feature Importance Scores for Automated Feature Engineering
by: Dong, Yihe, et al.
Published: (2024)

SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution
by: Wang, Hanlin, et al.
Published: (2025)

Automated Cyber Defense with Generalizable Graph-based Reinforcement Learning Agents
by: King, Isaiah J., et al.
Published: (2025)

Dual Active Learning for Reinforcement Learning from Human Feedback
by: Liu, Pangpang, et al.
Published: (2024)

Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity
by: Gu, Hanlin, et al.
Published: (2024)

Dual-Agent Deep Reinforcement Learning for Dynamic Pricing and Replenishment
by: Zheng, Yi, et al.
Published: (2024)

Actor-Accelerated Policy Dual Averaging for Reinforcement Learning in Continuous Action Spaces
by: Gao, Ji, et al.
Published: (2026)

Heterogeneity-aware Personalized Federated Learning via Adaptive Dual-Agent Reinforcement Learning
by: Chen, Xi, et al.
Published: (2025)

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

A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning
by: Fu, Yonggan, et al.
Published: (2021)

StackFeat RL: Reinforcement Learning over Iterative Dual Criterion Feature Selection for Stable Biomarker Discovery
by: Yermekov, A., et al.
Published: (2026)

NDRL: Cotton Irrigation and Nitrogen Application with Nested Dual-Agent Reinforcement Learning
by: Xu, Ruifeng, et al.
Published: (2025)

Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training
by: Hu, Pihe, et al.
Published: (2024)

Continual Offline Reinforcement Learning via Diffusion-based Dual Generative Replay
by: Liu, Jinmei, et al.
Published: (2024)

ReinforceGen: Hybrid Skill Policies with Automated Data Generation and Reinforcement Learning
by: Zhou, Zihan, et al.
Published: (2025)