Special Topics in Deep Reinforcement Learning

Special Topics in Deep Reinforcement Learning

Reinforcement Learning (RL) is a popular sub-discipline of Machine Learning for problems that require strategies to solve complex tasks such as board games, scheduling problems, or other discrete optimization problems. Deep Reinforcement Learning (DRL) is the combination of Reinforcement Learning with Neural Networks. 

In this seminar, we will first cover the most important algorithms of Deep Reinforcement Learning. Afterwards, we will dive deeper and have a look on special topics that our group is conducting research on. In particular, we will consider exploration techniques, agentic RL, and AI planning.

The kick-off will take place on 21.04.26, 13:00 at DFKI D3.4 in room Reuse (-2.17). Participation is mandatory.