The Game That Learns

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By the 1950s, science fiction was beginning to become reality: machines didn’t just calculate; they began to learn. Machine calculating was out. Machine learning was in. But we had to start small.

Donald Michie’s “Machine Educable Noughts And Crosses Engine” -- MENACE -- was composed of 304 separate matchboxes that each depicted a possible state of a checker game. MENACE eventually learned to play perfectly, and we replicate and explain that process with Shreksapawn, our adaptation of Martin Gardner’s MENACE-inspired game of Hexapawn.

The goal of MENACE and Hexapawn was to determine how to get machines to learn, and eventually to get them to think. As we realized how the simplest computers could learn to play games perfectly, we may have stumbled on the secret to humans playing the game of life perfectly... or at least getting a tiny bit closer to perfection every day.

By harnessing math, the human intellect, and a bag full of crafting supplies, we can gain just a little glimpse into how intelligence actually works -- whether it’s human or artificial.

*** SOURCES ***

“How to Build a Game-Learning Machine and Then Teach It to Play and Win,” Martin Gardner, Scientific American: http://cs.williams.edu/~freund/cs136-073/GardnerHexapawn.pdf

Matthew Scroggs’ MENACE Simulator: http://www.mscroggs.co.uk/menace/

MENACE: Machine Educable Noughts And Crosses Engine: http://www.mscroggs.co.uk/blog/19
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Hosted, Produced, And Edited by Kevin Lieber
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Research And Writing by Matthew Tabor
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VFX By Eric Langlay
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Видео The Game That Learns канала Vsauce2