Technical Workshop Series - An Introduction to Reinforcement Learning (2nd Offering) by: Xiaofeng Liu (Michael)

Reinforcement learning (RL) is the training of machine learning models to make a sequence of decisions. The agent learns to achieve a goal in an uncertain, potentially complex environment. In reinforcement learning, artificial intelligence faces a game-like situation. The computer employs trial and error to come up with a solution to the problem.  This workshop will introduce the main concepts of Reinforcement Learning (RL) with examples.

 

•             What is the difference between Reinforcement Learning and other machine learning methods? 

•             Components of RL

•             RL learning process

•             Example of RL

•             Q&A

 

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Xiaofeng (Michael) is a PhD Candidate in Computer Science. His main research interests are mainly focused on Congestion Control for V2V communication in VANET (Vehicular Ad hoc Network).