[HTML][HTML] A review of green artificial intelligence: Towards a more sustainable future
Green artificial intelligence (AI) is more environmentally friendly and inclusive than
conventional AI, as it not only produces accurate results without increasing the …
conventional AI, as it not only produces accurate results without increasing the …
Reinforcement learning based resource management for fog computing environment: Literature review, challenges, and open issues
In the IoT-based systems, the fog computing allows the fog nodes to offload and process
tasks requested from IoT-enabled devices in a distributed manner instead of the centralized …
tasks requested from IoT-enabled devices in a distributed manner instead of the centralized …
Whole building energy model for HVAC optimal control: A practical framework based on deep reinforcement learning
Whole building energy model (BEM) is a physics-based modeling method for building
energy simulation. It has been widely used in the building industry for code compliance …
energy simulation. It has been widely used in the building industry for code compliance …
Ten questions concerning reinforcement learning for building energy management
As buildings account for approximately 40% of global energy consumption and associated
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …
[HTML][HTML] Experimental evaluation of model-free reinforcement learning algorithms for continuous HVAC control
Controlling heating, ventilation and air-conditioning (HVAC) systems is crucial to improving
demand-side energy efficiency. At the same time, the thermodynamics of buildings and …
demand-side energy efficiency. At the same time, the thermodynamics of buildings and …
Toward a systematic survey for carbon neutral data centers
Data centers are experiencing unprecedented growth as the fourth industrial revolution's
supporting pillars and the engine for the future digitalized world. However, data centers are …
supporting pillars and the engine for the future digitalized world. However, data centers are …
Artificial intelligence to support the integration of variable renewable energy sources to the power system
The power sector is increasingly relying on variable renewable energy sources (VRE)
whose share in energy production is expected to further increase. A key challenge for …
whose share in energy production is expected to further increase. A key challenge for …
Cost-aware job scheduling for cloud instances using deep reinforcement learning
As the services provided by cloud vendors are providing better performance, achieving auto-
scaling, load-balancing, and optimized performance along with low infrastructure …
scaling, load-balancing, and optimized performance along with low infrastructure …
Gnu-rl: A precocial reinforcement learning solution for building hvac control using a differentiable mpc policy
Reinforcement learning (RL) was first demonstrated to be a feasible approach to controlling
heating, ventilation, and air conditioning (HVAC) systems more than a decade ago …
heating, ventilation, and air conditioning (HVAC) systems more than a decade ago …
Building HVAC control with reinforcement learning for reduction of energy cost and demand charge
Energy efficiency remains a significant topic in the control of building heating, ventilation,
and air-conditioning (HVAC) systems, and diverse set of control strategies have been …
and air-conditioning (HVAC) systems, and diverse set of control strategies have been …