- Multi|agent reinforcement learning for online scheduling in smart ...🔍
- Multi agent reinforcement learning for online layout planning and ...🔍
- Multi|Agent Reinforcement Learning for Job Shop Scheduling in ...🔍
- A review of the applications of multi|agent reinforcement learning in ...🔍
- Deep Reinforcement Learning based Online Scheduling Policy for ...🔍
- Multi|Task Multi|Agent Reinforcement Learning for Real|Time ...🔍
- Reinforcement learning for online optimization of job|shop ...🔍
- A Review on Reinforcement Learning in Production Scheduling🔍
Multi|agent reinforcement learning for online scheduling in smart ...
Multi-agent reinforcement learning for online scheduling in smart ...
This paper presents new cyber-physical integration in smart factories for online scheduling of low-volume-high-mix orders.
Multi-agent reinforcement learning for online scheduling in smart ...
Semantic Scholar extracted view of "Multi-agent reinforcement learning for online scheduling in smart factories" by Tong Zhou et al.
Multi-agent reinforcement learning for online scheduling in smart ...
Multi-agent reinforcement learning for online scheduling in smart factories · List of references · Publications that cite this publication. Indoor Positioning ...
Multi agent reinforcement learning for online layout planning and ...
The job-shop scheduling problem (JSP) is a combinatorial optimization problem in which various manufacturing jobs consisting of operations are ...
Multi-Agent Reinforcement Learning for Job Shop Scheduling in ...
Han [45] presented a deep reinforcement learning (DRL) framework that leverages analytical graph scheduling to navigate the complex and dynamic production ...
A review of the applications of multi-agent reinforcement learning in ...
The DQN-based agents corresponding to different manufacturing components evaluate job priorities and schedule them via negotiation while continuously learning ...
Deep Reinforcement Learning based Online Scheduling Policy for ...
Abstract:Currently, there is a growing trend of outsourcing the execution of DNNs to cloud services. For service providers, managing ...
(PDF) Reinforcement learning for online optimization of job-shop ...
Based on deep reinforcement learning (RL), the smart scheduler autonomously learns to schedule manufacturing resources in real time and improve ...
A review of the applications of multi-agent reinforcement learning in ...
Luo et al. (2021a) presented a hierarchical RL (HRL) approach with two hierarchies for production scheduling in order to minimize the total ...
Multi-Task Multi-Agent Reinforcement Learning for Real-Time ...
The reinforcement learning training algorithm is designed based on a double-deep Q-network. Finally, the scheduling simulation environment is ...
Reinforcement learning for online optimization of job-shop ...
Based on deep reinforcement learning (RL), the smart scheduler autonomously learns to schedule manufacturing resources in real time and improve ...
A Review on Reinforcement Learning in Production Scheduling
Smart Scheduling for Flexible and Hybrid Production with Multi-Agent Deep. Reinforcement Learning. In: Proceedings of 2021 IEEE 2nd ...
A cooperative multi-agent deep reinforcement learning framework ...
A cooperative multi-agent deep reinforcement learning framework for real-time residential load scheduling · Abstract · References · Cited By · Index Terms.
Multi-agent system and reinforcement learning approach for ...
[32] introduces a reinforcement learning approach to enable agents to learn the environment to solve the scheduling problem. However, these methods do not cover ...
Knowledge graph-enhanced multi-agent reinforcement learning for ...
This is based on the premise that machine assignment preferences effectively could reduce the Reinforcement Learning search space. Specifically, ...
A Review of Reinforcement Learning Based Intelligent Optimization ...
[16] proposed a multi-agent framework combined with metaheuristics for ... agent reinforcement learning for online scheduling in smart factories, Robot.
Demand-Side Scheduling Based on Multi-Agent Deep Actor-Critic ...
Simulation results show that our online deep reinforcement learning method can reduce both the peak-to-average ratio of total energy consumed and the cost of ...
A multi‐objective multi‐agent deep reinforcement learning approach ...
This research study presents a multi-objective tunable deep reinforcement learning algorithm for demand-side management of household appliances.
Learning in multi-agent systems to solve scheduling problems
learning approach to residential appliance scheduling,” IET Smart ... Zhou, “Multi-agent deep reinforcement learning for online request scheduling in edge.
Single-Agent Reinforcement Learning and Multi-Agent ...
Single-agent reinforcement learning (SARL) virtualizes an agent interacting with the scheduling environment, learning a scheduling policy, and then making ...