Systems Science Friday Noon Seminar Series

Monte Carlo Tree Search

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Format

Video: MP4; File size: 157 MB; Duration: 50:23

Date

1-20-2023

Abstract

The Monte-Carlo Tree Search (MCTS) algorithm became prominent in the 2010s by facilitating the first AI players capable of human-level play in the game of Go. Most notably, it provided a key component of the DeepMind AlphaGo player that famously defeated Lee Sedol in a 5-game Go series in 2016. This talk will explain the MCTS algorithm and contextualize it by contrasting it with more traditional game techniques and other Monte-Carlo techniques.

Biographical Information

Nick Embrey is a recent graduate of the M.S. in Computer Science at Portland State University and received a graduate certificate in Computer Modeling & Simulation from the Systems Science program. Prior to attending Portland State University, he studied ancient Mediterranean literature and languages as an undergraduate and worked for several years as a software engineer. During his last few terms at PSU, he worked on a project with Bart Massey of the Computer Science department to create an MCTS AI player for the tabletop card game Dominion.

Subjects

Monte Carlo method, Dielectric measurements, Electromagnetic waves -- Scattering

Disciplines

Systems Science

Persistent Identifier

https://archives.pdx.edu/ds/psu/39227

Rights

© 2023 Nick Embry

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Monte Carlo Tree Search

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