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Past event ·

Search, Sample, Learn: Chess in the age of AlphaZero

D'Arcy Kenworthy
WhenFriday 7 November 2025
Who can comeStudents & postdocs

Undergraduate, master’s and PhD students, and postdocs.

Abstract

Early AI researchers focused on games like chess as a proving ground for machine intelligence. In this talk we’ll trace the evolution of chess robots from expert-encoded knowledge to AlphaZero in 2017, which learned chess from scratch in 9 hours of self-play and crushed the best traditional engines. We’ll walk through the key concepts of computer chess including minimax search, alpha-beta pruning, Monte Carlo tree search, and neural networks. We’ll wrap up with how these methods have since been applied to more complex games like poker, Go, and StarCraft.

Image accompanying Search, Sample, Learn: Chess in the age of AlphaZero
Image provided by the speaker.