The AI lab co-organises the next ACAI summerschool on Reinforcement Learning

We’re happy to announce that this year’s ACAI summer school will be solely devoted to Reinforcement Learning (basics and recent developments), a branch of machine learning that focuses on learning from interaction with an uncertain environment and potential peers. The school will be organized from 7th until 14th October 2017 in Nieuwpoort, Belgium.
Recent progress and successes, such as e.g. AlphaGo, have revived strong interest in Reinforcement Learning (RL) and have pushed the boundaries of the state-of-the-art. Unfortunately, in typical machine learning courses and text books only the very basics of RL are covered. To bridge the gap between basic RL algorithms, such as for instance Q-learning, and the RL architecture that allowed to beat some of the best human Go players, this summerschool will introduce various advanced RL techniques, such as:  batch and policy search techniques,  shaping and inverse RL, RL for multi-agent systems and robotics, and Deep Reinforcement Learning. These topics will be taught by top scientists and experts in RL. 
Interested in learning more about RL? but unsure about your basic RL knowledge? No worries, we got you covered: you can opt for the additional two days before the actual start of the school to make sure you have the necessary background and skills before diving into the more advanced topics. 
We have chosen for an on-site approach, where all participants and lectures stay at the same location and spend a full week together to ‘learn' RL and jointly participate in social activities. If you want to know more about the school and the registration process: check out the website at
Organisers: Ann Nowe (VUB), Karl Tuyls (University of Liverpool), Robert Babuska (TUDelft)