On the use of quantum reinforcement learning in energy-efficiency scenarios

HIGHLIGHTS

• who: Eva Andrés et al. from the Department of Computer Science and Artificial Intelligence, ETSI Informática y de Telecomunicación, Universidad de Granada, C/Pdta Daniel Saucedo Aranda sn, Granada, Spain have published the Article: On the Use of Quantum Reinforcement Learning in Energy-Efficiency Scenarios, in the Journal: Energies 2022, 15, 6034. of /2022/
• what: The authors propose to study the benefits and limitations of quantum reinforcement learning to solve energyefficiency The authors use the Advantage Actor-Critic (A2C) training algorithm , whose designed loss function is described in Equation . In the work . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.