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Knowledge Base
Smart Droplets Knowledge Base  ·  Wageningen University

Lecture on Reinforcement Learning

Duration: 1 hour

Participants: 10 people

The lecture delves into the realm of policy approximation in Reinforcement Learning (RL), specifically focusing on the utilization of neural networks. It explores the concept of policy networks, which learn to map states to actions, enabling agents to make optimal decisions. The discussion also touches upon the integration of actor-critic methods, a powerful technique that combines policy gradient and value function estimation for efficient learning. Additionally, the lecture briefly highlights the potential application of RL in the domain of crop management, showcasing the versatility of these techniques in addressing real-world challenges.

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Project Coordination

Dr. Spyros Fountas

Associate Professor
  • Agricultural University of Athens
  • 75 Iera Odos Str. 11855, Athens, Greece
Project Communication

Grigoris Chatzikostas

RFF Partner
  • reframe.food
  • 20 Leontos Sofou str, 57001, Thermi Thessalonikis, Greece

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

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