The Conference for Machine Learning Innovation

Reinforcement Learning: a gentle Introduction and industrial Application

Session
Join the ML Revolution!
New date:
November 16 – 18, 2020
Register Now
Join the ML Revolution!
New date:
November 16 – 18, 2020
Register Now
Join the ML Revolution!
Register until July 2:
✓ Raspberry Pi or C64 Mini for free
✓ Save up to $310
✓ 10% team discount
Register Now
Join the ML Revolution!
Register until July 2:
✓ Raspberry Pi or C64 Mini for free
✓ Save up to $310
✓ 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
Tuesday, June 18 2019
10:15 - 11:15
Room:
Cuvillies 1

Reinforcement learning learns complex processes autonomously. No big data sets with the “right” answers are needed; the algorithms learn by experimenting. By using reinforcement learning, robots learn to walk, beat the world champion in Go, or fly a helicopter.

This talk shows “how” and “why” reinforcement learning algorithms work in an intuitive fashion, illustrating their inner-workings by the way a child learns to play a new game. We show what it takes to rephrase a real world problem as a reinforcement learning task and take a look at the challenges to bring it into production on 7000 client in 42 countries all around the world. 

Our industrial application is based on siphonic roof drainage systems. It warrants that large buildings like stadiums, airports, or shopping malls do not collapse during heavy rainfalls. Choosing the “right” diameters is difficult, requiring intuition and hydraulic expertise. As of today, no feasible, deterministic algorithm is known. Using reinforcement learning we were able to reduce the fail rate of our existing solution – based on classic supervised learning – by more than 70%.

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Munich Munich .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Singapore Singapore .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Berlin Berlin .

This Session Diese Session originates from the archive of stammt aus dem Archiv von MunichMunich . Take me to the current program of . Hier geht es zum aktuellen Programm von Munich Munich , Singapore Singapore or oder Berlin Berlin .

Behind the Tracks