Reinforcement Learning: Pac-Man

Manu Gopinathan

Malte Loller-Andersen

Half-day workshop - in English

Over the past few years, reinforcement learning (RL) has achieved promising results and it is currently being explored in a wide range of fields. In areas such as self driving cars, gaming and medicine, RL is the frontier of state-of-the-art results. In this workshop we will explore what the fuss is all about!

This workshop serves as an introduction to reinforcement learning where the participants will implement a Pac-Man agent. The Pac-Man agent will learn how to solve different maps using Q-learning and Deep Q-learning. We start out by exploring Q-learning, a cornerstone in RL. Expanding further, we continue on to deep Q-learning, which utilizes neural networks. The code is executed in the cloud on Jupyter notebooks, and for training the neural networks we use GPUs in the cloud. Everything is written in python.

If reinforcement learning has been a mysterious domain to you, this session will most likely leave you with a greater understanding of the process and aid you in how to set up projects of your own.

Primarily for: Developers

Participant requirements: Laptops