Cover Image

Deep Reinforcement Learning for Artificial Upwelling Energy Management

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Yiyuan, Fan, Wei
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DeepStock: Reinforcement Learning with Policy Regularizations for Inventory Management
by: Xie, Yaqi, et al.
Published: (2026)

Higher-Order Action Regularization in Deep Reinforcement Learning: From Continuous Control to Building Energy Management
by: Ahmed, Faizan, et al.
Published: (2026)

Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
by: Jiang, Jinyang, et al.
Published: (2024)

Energy-Efficient Deep Reinforcement Learning with Spiking Transformers
by: Uddin, Mohammad Irfan, et al.
Published: (2025)

Green Energy Management for Sustainable Data Centers Using Deep Reinforcement Learning
by: Bahi, Abderaouf, et al.
Published: (2025)

A Practical Introduction to Deep Reinforcement Learning
by: Sun, Yinghan, et al.
Published: (2025)

Meta-Reinforcement Learning for Building Energy Management System
by: Zhang, Huiliang, et al.
Published: (2022)

Deep Learning for Multivariate Time Series Imputation: A Survey
by: Wang, Jun, et al.
Published: (2024)

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility
by: Alvarez, Luis E., et al.
Published: (2024)

ORPR: An OR-Guided Pretrain-then-Reinforce Learning Model for Inventory Management
by: Zhao, Lingjie, et al.
Published: (2025)

A Safe Deep Reinforcement Learning Approach for Energy Efficient Federated Learning in Wireless Communication Networks
by: Koursioumpas, Nikolaos, et al.
Published: (2023)

Deep Reinforcement Learning for Traveling Purchaser Problems
by: Yuan, Haofeng, et al.
Published: (2024)

A Unified Deep Reinforcement Learning Approach for Close Enough Traveling Salesman Problem
by: Fan, Mingfeng, et al.
Published: (2025)

MTS: A Deep Reinforcement Learning Portfolio Management Framework with Time-Awareness and Short-Selling
by: Gu, Fengchen, et al.
Published: (2025)

An Invitation to Deep Reinforcement Learning
by: Jaeger, Bernhard, et al.
Published: (2023)

Energy-Based Transfer for Reinforcement Learning
by: Deng, Zeyun, et al.
Published: (2025)

A Deep Reinforcement Learning Approach to Battery Management in Dairy Farming via Proximal Policy Optimization
by: Ali, Nawazish, et al.
Published: (2024)

Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Network
by: Wu, Qiong, et al.
Published: (2024)

Structure in Deep Reinforcement Learning: A Survey and Open Problems
by: Mohan, Aditya, et al.
Published: (2023)

Causal-Paced Deep Reinforcement Learning
by: Cho, Geonwoo, et al.
Published: (2025)

Behavior-Consistent Deep Reinforcement Learning
by: Hussing, Marcel, et al.
Published: (2026)

Satisficing Exploration for Deep Reinforcement Learning
by: Arumugam, Dilip, et al.
Published: (2024)

Rethinking Plasticity in Deep Reinforcement Learning
by: He, Zhiqiang
Published: (2026)

Recursive Deep Inverse Reinforcement Learning
by: Ghanem, Paul, et al.
Published: (2025)

Understanding and Diagnosing Deep Reinforcement Learning
by: Korkmaz, Ezgi
Published: (2024)

Artificial Generals Intelligence: Mastering Generals.io with Reinforcement Learning
by: Straka, Matej, et al.
Published: (2025)

Reward Models in Deep Reinforcement Learning: A Survey
by: Yu, Rui, et al.
Published: (2025)

Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning
by: Xie, Sean, et al.
Published: (2022)

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
by: Zhang, Cong, et al.
Published: (2022)

Multi-Objective Reinforcement Learning for Water Management
by: Osika, Zuzanna, et al.
Published: (2025)

On the Role of DAG topology in Energy-Aware Cloud Scheduling : A GNN-Based Deep Reinforcement Learning Approach
by: Hattay, Anas, et al.
Published: (2026)

Learning Markov State Abstractions for Deep Reinforcement Learning
by: Allen, Cameron, et al.
Published: (2021)

Manifold-Constrained Energy-Based Transition Models for Offline Reinforcement Learning
by: Fang, Zeyu, et al.
Published: (2026)

Clustering-Based Weight Orthogonalization for Stabilizing Deep Reinforcement Learning
by: Ma, Guoqing, et al.
Published: (2025)

Advancing Generative Artificial Intelligence and Large Language Models for Demand Side Management with Internet of Electric Vehicles
by: Zhang, Hanwen, et al.
Published: (2025)

Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting
by: Fan, Wei, et al.
Published: (2024)

Deep Reinforcement Learning with Task-Adaptive Retrieval via Hypernetwork
by: Jin, Yonggang, et al.
Published: (2023)

Deep Reinforcement Learning with Gradient Eligibility Traces
by: Elelimy, Esraa, et al.
Published: (2025)

A Survey on Explainable Deep Reinforcement Learning
by: Cheng, Zelei, et al.
Published: (2025)

Fast Value Tracking for Deep Reinforcement Learning
by: Shih, Frank, et al.
Published: (2024)