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A Machine-Learning Approach to Computer Go, Jeffrey Bagdis, 2007. Minimalism in Ubiquitous Interface Design Wren, C. and Reynolds, C. (2004) Personal and Ubiquitous Computing, 8(5), pages 370–374. Video of computer Go vision system in operation shows interaction and users exploring Joseki and Fuseki.
Decommissioned AlphaGo backend rack. Go is considered much more difficult for computers to win than other games such as chess, because its strategic and aesthetic nature makes it hard to directly construct an evaluation function, and its much larger branching factor makes it prohibitively difficult to use traditional AI methods such as alpha–beta pruning, tree traversal and heuristic search.
There is an abundance of go software available to support players of the game of Go.This includes software programs that play Go themselves, programs that can be used to view and/or edit game records and diagrams, programs that allow the user to search for patterns in the games of strong players and programs that allow users to play against each other over the Internet.
Subsequent log-ins will start with Tad and Dot coming on-screen and calling Scout into view before leaving. From here, the main menu appears and the user is given access to four built-in games, the cartridge game if its present, and Scout's dog house, in which the user can go to interact with Scout and the multiple items inside it.
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AlphaGo Zero is a version of DeepMind's Go software AlphaGo.AlphaGo's team published an article in Nature in October 2017 introducing AlphaGo Zero, a version created without using data from human games, and stronger than any previous version. [1]
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