Mini-course "Introduction to reinforcement learning" by HDI Lab Academic Supervisor, Professor Eric Moulines
On April 16, 23 we invite you to join the 2-day mini-course "Introduction to reinforcement learning" by Eric Moulines (Ecole Polytechnique, HSE).
Time : April 16 and 23, 17:00 - 19:00
Location : CS HSE, Kochnovkiy proezd 3, room 205 (April 16), room 503 (April 23)
The minicourse is an elementary introduction of reinforcement learning. We will formalize the problem of reinforcement learning using ideas from dynamical systems theory, specifically, as the optimal control of incompletely-known Markov decision processes. A learning agent must be able to sense the state of its environment to some extent and must be able to take actions that affect the state. The agent also must have a goal or goals relating to the state of the environment. Markov decision processes are intended to include just these three aspects—sensation, action, and goal—in their simplest possible forms without trivializing any of them. Any method that is well suited to solving such problems we consider to be a reinforcement learning method. The course is an elementary introduction covering: