Real-world sequential decision-making tasks are generally complex, requiring trade-offs
between multiple, often conflicting, objectives. Despite this, the majority of research in …

Turbines in a wind farm dynamically influence each other through wakes. Therefore trade-
offs exist between energy output of upstream turbines and the health of downstream …

We study the multi-agent multi-armed bandit (MAMAB) problem, where agents are factored
into overlap** groups. Each group represents a hyperedge, forming a hypergraph over …

Wind farms suffer from so-called wake effects: when turbines are located in the wind
shadows of other turbines, their power output is substantially reduced. These losses can be …

Abstract While Reinforcement Learning (RL) has already proven successful in performing
complex tasks, such as controlling large-scale epidemics, mitigating influenza and playing …

Many real-world problems contain multiple objectives and agents, where a trade-off exists
between objectives. Key to solving such problems is to exploit sparse dependency …

Calibrating analytical wake models for wind farm yield assessment and wind farm flow
control presents significant challenges. This study provides a robust methodology for the …

This work presents a robust methodology for calibrating analytical wake models, as
demonstrated on the velocity deficit parameters of the Gauss–curl hybrid model using 4 …

Wind is a renewable energy source that has become more important in recent years. Wind
turbines are equipped with a SCADA system, which allows for remote supervision of the …

This article considers a distributed Thompson sampling algorithm for a cooperative
multiplayer multiarmed bandit problem. We consider a multiagent system in which each …