Reinforcement Learning in Scala
Please log in to watch this conference skillscast.
Next you'll implement some of these concepts in Scala, starting from scratch and working step by step towards an implementation of 'Q-learning' – a popular RL technique for learning policies. You'll structure your code using type classes to separate the generic Q-learning framework from the specifics of any particular problem we want to model.
You will also learn how to train an agent using your Q-learning implementation, and finally Chris will demonstrate the result of the training: the computer successfully playing a simple game.
YOU MAY ALSO LIKE:
- Writing an SBT Plugin (SkillsCast recorded in February 2019)
- ScalaCon 2021: November Edition (Online Conference on 2nd - 5th November 2021)
- Journey to the Centre of the JVM (SkillsCast recorded in May 2021)
- Connecting the dots - building and structuring a functional application in Scala (SkillsCast recorded in May 2021)
Thank you to our sponsors and partners
Platinum
Gold
Silver
Bronze
Partners
Reinforcement Learning in Scala
Chris Birchall
Chris is a principal software developer at OVO Energy, where he looks after authentication and personal data as a member of the Identity team. He is the author of the ScalaCache library. He has been using Scala for work and play since 2010.