2023
DOI: 10.1016/j.patcog.2023.109436
|View full text |Cite
|
Sign up to set email alerts
|

Multi-agent dueling Q-learning with mean field and value decomposition

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2025
2025

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(1 citation statement)
references
References 20 publications
0
1
0
Order By: Relevance
“…The reliability evaluation methods for offshore wind power mainly include Monte Carlo simulation, analytical methods, and these include a range of artificial intelligence algorithms. Ding Q focuses on the stability of barge type floating offshore wind turbine (FOWT), and this article aims to study the effectiveness of passive structural control by installing tuned mass damper (TMD) in the engine room [11]. Amirhossein Sajadi proposes a probabilistic method for reassessing the fatigue design rules of offshore wind turbine concrete structures, which may help optimize structural design and further reduce the cost of offshore wind energy [12].…”
Section: 1reliability Enhancement Strategy For Offshore Wind Powermentioning
confidence: 99%
“…The reliability evaluation methods for offshore wind power mainly include Monte Carlo simulation, analytical methods, and these include a range of artificial intelligence algorithms. Ding Q focuses on the stability of barge type floating offshore wind turbine (FOWT), and this article aims to study the effectiveness of passive structural control by installing tuned mass damper (TMD) in the engine room [11]. Amirhossein Sajadi proposes a probabilistic method for reassessing the fatigue design rules of offshore wind turbine concrete structures, which may help optimize structural design and further reduce the cost of offshore wind energy [12].…”
Section: 1reliability Enhancement Strategy For Offshore Wind Powermentioning
confidence: 99%