Faculty Advisor

Sarkozy, Gabor N

Center

BUDAPEST / Budapest, Hungary

Abstract

In March 2016, AlphaGo, a computer Go program developed by Google DeepMind, won a 5-game match against Lee Sedol, one of the best Go players in the world. Its victory marks a major advance in the field of computer Go. However, much remains to be done. There is a gap between the computational power AlphaGo used in the match and the computational power available to the majority of computer users today. Further, the communication between two of the techniques used by AlphaGo, neural networks and Monte Carlo Tree Search, can be improved. We investigate four different approaches towards accomplishing this end, with a focus on methods that require minimal computational power. Each method shows promise and can be developed further.

Publisher

Worcester Polytechnic Institute

Date Accepted

April 2016

Major

Computer Science

Major

Mathematical Sciences

Project Type

Major Qualifying Project

Accessibility

Unrestricted

Advisor Department

Computer Science

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