Abstracts

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Hi all,
Pedro Tsividis will be presenting at ML Tea next Monday (?12/12?; talk details below).

As usual, drinks and snacks will be served.

Hope to see you there!

- ?Jonathan

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Title: Toward human-level learning of Atari games
Date: Monday, November 28, 2016
Time: 4:30 to 5:00 PM
Location: G4 lounge (32-G475A)

Abstract

Atari games are an excellent testbed for studying intelligent behavior, as they offer a range of tasks that differ widely in their visual representation, game dynamics, and goals presented to an agent. The last two years have seen a spate of research into artificial agents that use a single algorithm to learn to play these games. The best of these artificial agents perform at better-than-human levels on most games, but require dozens or hundreds of hours of game-play experience to produce such behavior. Humans, on the other hand, can learn to perform well on these tasks in a matter of minutes. I will present data on human learning trajectories for several Atari games and test several hypotheses about the mechanisms that lead to such rapid learning.

Thanks to our sponsor: ML Tea refreshments are provided by FeatureX, a machine learning startup in Kendall Sq. http://www.featurex.ai
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