The Special Interest Group in Reinforcement Learning is concerned with how an intelligent agent ought to take actions in a dynamic environment in order to maximize the cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning, and an interdisciplinary area of machine learning and optimal control. The main topics of interest of this Group are Model-Free Reinforcement Learning, Model-Based Reinforcement Learning, Bio-Inspired Reinforcement Learning and Quantum Reinforcement Learning.

Board Members

• Radu Grosu
• Clemens Heitzinger
• Benedikt Hartl