Copertina

Decentralized Coordination of Distributed Energy Resources through Local Energy Markets and Deep Reinforcement Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	May, Daniel, Taylor, Matthew, Musilek, Petr
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Systems and Control Artificial Intelligence Machine Learning Multiagent Systems
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Transactive Local Energy Markets Enable Community-Level Resource Coordination Using Individual Rewards
di: May, Daniel C., et al.
Pubblicazione: (2024)

VAE-GAN Based Price Manipulation in Coordinated Local Energy Markets
di: Mukherjee, Biswarup, et al.
Pubblicazione: (2025)

Cooperative Cruising: Reinforcement Learning-Based Time-Headway Control for Increased Traffic Efficiency
di: Veksler, Yaron, et al.
Pubblicazione: (2024)

Improving Mixed-Criticality Scheduling with Reinforcement Learning
di: El-Mahdy, Muhammad, et al.
Pubblicazione: (2025)

Learning Team-Based Navigation: A Review of Deep Reinforcement Learning Techniques for Multi-Agent Pathfinding
di: Chung, Jaehoon, et al.
Pubblicazione: (2023)

Systematic Analyses of Reinforcement Learning Controllers in Signalized Urban Corridors
di: Song, Xiaofei, et al.
Pubblicazione: (2026)

Distributed Management of Fluctuating Energy Resources in Dynamic Networked Systems
di: Cheng, Xiaotong, et al.
Pubblicazione: (2024)

IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
di: Jayawardana, Vindula, et al.
Pubblicazione: (2024)

AoI-Aware Resource Allocation with Deep Reinforcement Learning for HAPS-V2X Networks
di: Ince, Ahmet Melih, et al.
Pubblicazione: (2025)

Hierarchical Policy-Gradient Reinforcement Learning for Multi-Agent Shepherding Control of Non-Cohesive Targets
di: Covone, Stefano, et al.
Pubblicazione: (2025)

Balancing Specialization and Centralization: A Multi-Agent Reinforcement Learning Benchmark for Sequential Industrial Control
di: Maus, Tom, et al.
Pubblicazione: (2025)

DeMuon: A Decentralized Muon for Matrix Optimization over Graphs
di: He, Chuan, et al.
Pubblicazione: (2025)

Bayesian Critique-Tune-Based Reinforcement Learning with Adaptive Pressure for Multi-Intersection Traffic Signal Control
di: Duan, Wenchang, et al.
Pubblicazione: (2024)

Multi-Objective Optimization Using Adaptive Distributed Reinforcement Learning
di: Tan, Jing, et al.
Pubblicazione: (2024)

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers
di: Naug, Avisek, et al.
Pubblicazione: (2025)

CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control
di: Zeng, Jinwei, et al.
Pubblicazione: (2024)

Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies
di: DeWeese, Alex, et al.
Pubblicazione: (2024)

Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets
di: Salazar-Pena, Nelson, et al.
Pubblicazione: (2026)

JCAS-MARL: Joint Communication and Sensing UAV Networks via Resource-Constrained Multi-Agent Reinforcement Learning
di: Guven, Islam, et al.
Pubblicazione: (2026)

Coordination Matters: Evaluation of Cooperative Multi-Agent Reinforcement Learning
di: Cardei, Maria Ana, et al.
Pubblicazione: (2026)

Peer-to-Peer Energy Trading of Solar and Energy Storage: A Networked Multiagent Reinforcement Learning Approach
di: Feng, Chen, et al.
Pubblicazione: (2024)

Offline and Distributional Reinforcement Learning for Radio Resource Management
di: Eldeeb, Eslam, et al.
Pubblicazione: (2024)

Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics
di: Magnino, Lorenzo, et al.
Pubblicazione: (2025)

Decentralizing Multi-Agent Reinforcement Learning with Temporal Causal Information
di: Corazza, Jan, et al.
Pubblicazione: (2025)

Heterogeneous Multi-Agent Reinforcement Learning for Zero-Shot Scalable Collaboration
di: Guo, Xudong, et al.
Pubblicazione: (2024)

CoMIX: A Multi-agent Reinforcement Learning Training Architecture for Efficient Decentralized Coordination and Independent Decision-Making
di: Minelli, Giovanni, et al.
Pubblicazione: (2023)

Deep Reinforcement Learning for Multi-Agent Coordination
di: Aina, Kehinde O., et al.
Pubblicazione: (2025)

DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
di: Guillen-Perez, Antonio, et al.
Pubblicazione: (2025)

Learning a Stable, Safe, Distributed Feedback Controller for a Heterogeneous Platoon of Autonomous Vehicles
di: Shaham, Michael H., et al.
Pubblicazione: (2024)

Deep Reinforcement Learning Agents for Strategic Production Policies in Microeconomic Market Simulations
di: Garrido-Merchán, Eduardo C., et al.
Pubblicazione: (2024)

ReLMXEL: Adaptive RL-Based Memory Controller with Explainable Energy and Latency Optimization
di: Sai, Panuganti Chirag, et al.
Pubblicazione: (2026)

Together We Rise: Optimizing Real-Time Multi-Robot Task Allocation using Coordinated Heterogeneous Plays
di: Pal, Aritra, et al.
Pubblicazione: (2025)

Reinforcement Learning Enabled Peer-to-Peer Energy Trading for Dairy Farms
di: Shah, Mian Ibad Ali, et al.
Pubblicazione: (2024)

Sensor to Pixels: Decentralized Swarm Gathering via Image-Based Reinforcement Learning
di: Koifman, Yigal, et al.
Pubblicazione: (2026)

Reward-Independent Messaging for Decentralized Multi-Agent Reinforcement Learning
di: Yoshida, Naoto, et al.
Pubblicazione: (2025)

A Semi Centralized Training Decentralized Execution Architecture for Multi Agent Deep Reinforcement Learning in Traffic Signal Control
di: Rezaali, Arash, et al.
Pubblicazione: (2025)

Mean-Field Control on Sparse Graphs: From Local Limits to GNNs via Neighborhood Distributions
di: Schmidt, Tobias, et al.
Pubblicazione: (2026)

Settling Decentralized Multi-Agent Coordinated Exploration by Novelty Sharing
di: Jiang, Haobin, et al.
Pubblicazione: (2024)

Fully Decentralized Cooperative Multi-Agent Reinforcement Learning: A Survey
di: Jiang, Jiechuan, et al.
Pubblicazione: (2024)

Goal-Oriented Multi-Agent Reinforcement Learning for Decentralized Agent Teams
di: Du, Hung, et al.
Pubblicazione: (2025)