====== 10 Reinforcement Learning III ======

  * State values during a random walk
  * Approximation minimizing least squares error (LSQ)
  * Approximative Q-learning

===== Exercise for bonus points =====

  * Calculate state values during a random walk policy
  * 0.5 points
  * submit your solution to [[https://cw.felk.cvut.cz/brute/|BRUTE]] **lab10quiz** by May 04, midnight
  * format: text file, photo of your solution on paper, pdf - what is convenient for you
  * solution will be discussed on the next lab
  * Students with their family name starting from A to K (included) have to solve and upload {{ :courses:be5b33kui:labs:weekly:random_walk.pdf |subject A}} , while students with family name from L to Z have to solve and upload {{ :courses:be5b33kui:labs:weekly:random_walk.pdf |subject B}}.

> {{page>courses:be5b33kui:internal:quizzes#state_values_for_a_random_walk}}


===== Exercise II / Solving together during interactive lab =====

  * Approximation minimizing least squares error (LSQ)
  * Approximative Q-learning
  * {{:courses:be5b33kui:labs:weekly:learning_by_approximation.pdf |(see pdf)}}