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Simulating games

In this step, we look at the relationship between AI and simulation games.
The question is if I can get a robot to do things that appear to be human he’s just doing something that appears to be human, he doesn’t know consciousness. So, I do a little bit of research on emotion recognition. So, I think I can get a robot to recognise emotions, if I can get it say, if I recognise you were sad, it does a little dance to make you happy, it doesn’t really know what sad and happy are, it’s just recognising them and producing play behaviours. So, I think the contention is it might do exactly the same as what a human being would do, but does it really understand what we’re doing.
So, our robot, you know, it created activations patterns that were similar or you know, a very abstract way to a primate and it did work out what the difference between go were if I put it at different points in the room. But still it hasn’t got that consciousness of itself that we would class as real AI so maybe in the future if the robot becomes conscious of itself and get into all of these issues then of do robots deserve to be treated as a conscious object or a conscious person but now I think the little, the problem that probably you’re referring to us just because it looks human, or it does things that are human, it doesn’t make it human.
So, I think they’re probably the issues to be dealt with in a very abstract way.

In the video above, Dr Mark Elshaw talks about his experience of participating in the British Machine Intelligence Award. His video covers some key themes of this step, especially how the games humans play have been simulated by machines.

In particular, we explore where machines have shown better performance than humans in a series of games.

Machines surpassing humans


Following Turing’s work and his earlier idea of using chess to examine if a machine could play as well as a poor human player, in 1958, Herbert Newell and Allen Simon predicted that a computer would become world chess champion within 10 years. The prediction came true but within 30 years when IBM’s machine, Deep Blue beat the world chess grandmaster, Gary Kasparov, in 1997. See IBM (n.d.) Deep Blue.

Final Jeopardy!

In 2011, IBM pushed the boundaries of machine intelligence further when IBM’s Watson machine beat two human contestants in a general knowledge quiz show on American TV: Final Jeopardy! The format of this quiz show presents the answers and the challenge is for the humans to give what they believe the question is for that answer. This achievement has boosted interest and research funding in artificial intelligence. See Best (2013) ‘IBM Watson: The Inside Story of How the Jeopardy-Winning Supercomputer Was Born, and What it Wants to Do Next’.

Alpha Go

In 2016, another human vs machine challenge saw Google’s DeepMind AlphaGo algorithm beat the South Korean GO game champion Lee Sedol. See DeepMind (2016) ‘The Google DeepMind Challenge’ Match.


In July 2019, Carnegie Mellon University, using Facebook’s AI, ‘beat six professionals in a six-player poker game’. See an abstract of a paper describing this game Brown and Sandholm (2019) ‘Superhuman AI for Multiplayer Poker’.

Your task

Going back to Dr Mark Elshaw’s video, discuss why you think Turing evolved his chess-playing imitation game to a linguistic test?
Do you feel it unfairly binds progress in artificial intelligence with human language?

Further reading

Fischler M.A. and Firschein, O.I. (1987). Intelligence: the Eye, the Brain, and the Computer. Addison-Wesley

IBM. (n.d.). A Computer Called Watson. Icons of Progress


Best, J. (2013). IBM Watson: The Inside Story of How the Jeopardy-Winning Supercomputer Was Born, and What it Wants to Do Next. Techrepublic

Brown, N. and Sandholm, T. (2019). Superhuman AI for Multiplayer Poker. Science

DeepMind. (2016). The Google DeepMind Challenge Match. AlphaGo Korea

IBM. (n.d.). Deep Blue. Icons of Progress

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