Title: “Learning how the brain learns”: The successor representation in reinforcement learning
Date/Time : 8 October 2018 (Monday), 6.00pm to 7.00pm
Venue : NUS Faculty of Engineering, Lecture Theater 7A (LT7A)
Speaker : Fred Almeida
Abstract:
Artificial intelligence learns as we humans do – by trial and error. Our experiences teach us valuable lessons
which can be applied to new situations. Over time the surrounding world starts to make sense to us and we
can be entrusted with more demanding tasks like driving a car. For an AI agent, this learning takes place in a
simulation but the principles are the same. To build an AI capable of human level performance, Ascent is
bringing the most recent research advancements in the field to market. Technologies we work with include
deep reinforcement learning, generative models and transfer learning. We are constantly testing new
models and applying the best research to create cutting-edge artificial intelligence. Artificial Intelligence
algorithms are not developed in the same way as traditional software. AIs are trained in simulations through
trial and error. Behaviour that produces better outcomes for the AI agent are reinforced while adverse
choices are discouraged. This is called reinforcement learning. This approach allows the AI to work out for
itself which behaviours are most useful to master. We control the learning framework of the simulated
environment and let the AI agent determine optimal behaviour models on its own.

 

About the speaker:
Fred Almeida is the founder of Ascent Robotics, developing autonomous robotics in Tokyo. He comes from
a background in Philosophy, Mathematics and is attending Harvard Business School. He spends his free time
mostly on planes reading papers.

Please register your attendance at the following link by 4 October 2018:
https://goo.gl/forms/3HKuCqVC05i3SJro1

For enquiry, please email: robotics@nus.edu.sg

Click here for pdf with more details.

Click here for the webcast of the seminar.

 

Supported by NUS-NVIDIA JOINT LAB