Hey SIGAI, We're beginning our Unit 2 on Advanced Topics with a lecture on evolutionary computation by Dr. Annie Wu from UCF's Computer Science Department! She'll be giving the introductory lecture she gives to her graduate students in her Evolutioanry Computation course here at UCF. There will be no slides for this lecture so if you're curious to know, come out! It is going to be a great primer for our following lecture on neuroevolution. More about Dr. Wu: Dr. Wu is the Director of the Evolutionary Computation Lab at UCF and an Associate Professor in the Department of Computer Science. Find more here: http://www.cs.ucf.edu/~aswu/
We all remember when DeepMind’s AlphaGo beat Lee Sedol, but what actually made the program powerful enough to outperform an international champion? In this lecture, we’ll dive into the mechanics of reinforcement learning and its applications.
We all remember when DeepMind’s AlphaGo beat Lee Sedol, but what actually made the program powerful enough to outperform an international champion? In this lecture, we’ll dive into the mechanics of reinforcement learning and its applications.
It's easy enough to navigate a 16x16 maze with tables and some dynamic programming, but how exactly do we extend that to play video games with millions of pixels as input, or board games like Go with more states than particals in the observable universe? The answer, as it often is, is deep reinforcement learning.
We agree with Lake and colleagues on their list of key ingredients for building humanlike intelligence, including the idea that model-based reasoning is essential. However, we favor an approach that centers on one additional ingredient: autonomy. In particular, we aim toward agents that can both build and exploit their own internal models, with minimal human hand-engineering. We believe an approach centered on autonomous learning has the greatest chance of success as we scale toward real-world complexity, tackling domains for which ready-made formal models are not available. Here we survey several important examples of the progress that has been made toward building autonomous agents with humanlike abilities, and highlight some outstanding challenges.