The Conference for Machine Learning Innovation

Reinforcement Learning and Imitation Learning Workshop

Workshop
Join the ML Revolution!
Register until March 5:
✓ML Intro Day for free
✓Save up to 500 €
✓10 % Team Discount
Register Now
Join the ML Revolution!
Register until March 5:
✓ML Intro Day for free
✓Save up to 500 €
✓10 % Team Discount
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Infos
Booking note:
Reinforcement Learning Workshop

Deep Reinforcement-Learning (RL) in various decision-making tasks of Machine-Learning (ML) provides effective
results with an agent/ agents learning from observing an environment and gaining rewards and punishments. RL as a
great technique in ML shows its ability to be utilized in different time-series and Computer Vision-based (CV)
projects like autonomous driving, robotics, traffic control, web system configuration, recommendation systems, and
game applications. In complex environments where RL underperforms as a consequence of extensive demonstration
information in long-horizon problems, Imitation Learning (IL) offers a promising solution for the challenges. In IL,
the learning process can take advantage of human-sourced assistance and/or control over the agent and environment.
The purpose of this talk is to provide an introduction to Deep RL and IL at a level easily understood by students
and researchers in a wide range of disciplines. Also, we will overview different RL and IL techniques and methods
as long as discuss how they are utilized to improve the performance of different tasks. Also, we cover the usage of
RL and IL in CV, NLP and time-series tasks.

Take me to the full program of Zum vollständigen Programm von Munich Munich .

This Session belongs to the Diese Session gehört zum Programm vom MunichMunich program. Take me to the program of . Hier geht es zum Programm von Berlin Berlin .

This Session belongs to the Diese Session gehört zum Programm vom MunichMunich program. Take me to the program of . Hier geht es zum Programm von Singapore Singapore .

This Session Diese Session belongs to the gehört zum Programm von MunichMunich program. Take me to the current program of . Hier geht es zum aktuellen Programm von Munich Munich , Berlin Berlin or oder Singapore Singapore .

Behind the Tracks