Beyond games: a systematic review of neural Monte Carlo tree search applications
The advent of AlphaGo and its successors marked the beginning of a new paradigm in
playing games using artificial intelligence. This was achieved by combining Monte Carlo …
playing games using artificial intelligence. This was achieved by combining Monte Carlo …
Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions
Machine scheduling aims to optimize job assignments to machines while adhering to
manufacturing rules and job specifications. This optimization leads to reduced operational …
manufacturing rules and job specifications. This optimization leads to reduced operational …
Are You Diligent, Inefficient, or Malicious? A Self-Safeguarding Incentive Mechanism for Large Scale-Federated Industrial Maintenance Based On Double Layer …
Fault prediction is an important application in the Industrial Internet of Things (IIoT) to ensure
the safety of industrial systems and factories. Currently, deep-learning-based fault prediction …
the safety of industrial systems and factories. Currently, deep-learning-based fault prediction …
Federated Learning Incentive Mechanism Setting in UAV-Assisted Space–Terrestrial Integration Networks
C Zhu, M Sui, H Zhao, K Chen, T Zhang, C Bao - Electronics, 2024 - mdpi.com
The UAV-assisted space–terrestrial integrated network provides extensive coverage and
high flexibility in communication services. UAVs and ground terminals collaborate to train …
high flexibility in communication services. UAVs and ground terminals collaborate to train …
[PDF][PDF] Solving Job Shop Problems with Neural Monte Carlo Tree Search.
Job shop scheduling is a common NP-hard problem that finds many applications in
manufacturing and beyond. A variety of methods to solve job shop problems exist to address …
manufacturing and beyond. A variety of methods to solve job shop problems exist to address …