AlphaGo: Computers and Game Playing: A Very Timely Lecture

Today (14:00, 07 Mar 2016 in F1A09 at the University of Nottingham Malaysia Campus) I am giving a two hour lecture on Computers and Game Playing.

This lecture could not have come at a better time.

At the end of January, Google’s DeepMind reported that AlphaGo had beaten the top European Go player (Fan Hui) 5-0. This was probably about ten years earlier than most people expected a computer to defeat a human expert at Go. This You Tube video gives a very good overview of the achievement.


This development is, in my view and the view of many others, one of the most significant landmarks since Gary Kasparov was defeated by Deep Blue in May 1997.

The defeat of Fan Hui has generated so much interest that the World’s best player (Lee Sedol) has agreed to play AlphaGo in March (9th – 15th) 2016.

My lecture is nicely sandwiched between the recent defeat and the upcoming match against the current best player in the world.

In the lecture I will still cover the material that I need to get across (such as mini-max, alpha-beta search) but it would be remiss of me not to talk about the recent successes of AlphaGo and the technologies that have led to this remarkable achievement.

Indeed, in my next lecture, I will be talking about Deep Blue (Chess), Chinook (Checkers) and Blondie24 (Checkers), where some of the methodologies that led to their successes will be discussed. No doubt AlphaGo will also get a mention and, by then, we should have some more knowledge about it it has performed against Lee Sedol.

It’s a great time to be a student who is interested in game playing and artificial intelligence!

Finally, a plug. I am the Editor-in-Chief of the IEEE Transactions of Computational Intelligence and AI in Games (TCIAIG) and we would welcome any articles that are motivated by the recent successes in Go.

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