David J. Wu

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David Jian Wu, an American computer scientist and computer games researcher and programmer, who balances a mixture of software development and research within the financial industry. He defended his B.Sc. degree in 2011 at Harvard College, Harvard University, delivering the thesis Move Ranking and Evaluation in the Game of Arimaa. David J. Wu is author of the Arimaa bot Sharp, and inspired by AlphaZero, the Go playing program KataGo.

=Sharp= The Arimaa playing bot Sharp won the 2015 Arimaa Challenge and the then $12,000 USD prize by defeating each of three top-ranked human players in a three game series. It already played the 2008 Arimaa computer tournament, and became runner-up behind David Fotland’s program Bomb, and further won the 2011 and 2014 tournaments but not the contest against the best human players of that time. Sharp's design was elaborated by its author in the 2015 ICGA Journal, Vol. 38, No. 1. It follows the same fundamental design as strong Chess programs, using an iterative deepening depth limited alpha-beta search and various enhancements within a parallel search algorithm conceptually similar to the dynamic tree splitting described by Robert Hyatt in 1994. Sharp further implements several Arimaa-specific search enhancements with four steps per move, such as static goal detection and capture generation, and continues to use and benefit greatly from a move ordering function developed in 2011 as described in Wu's thesis - the move ordering function is the result of training a slightly generalized Bradley-Terry model over thousands of expert Arimaa games to learn to predict expert player's moves, using the same optimization procedure described by Rémi Coulom for computer Go.

=KataGo= KataGo is a Go playing entity inspired by the AlphaZero approach of combining Deep learning with Monte-Carlo Tree Search (MCTS) using pure reinforcement learning aka self play to train the deep neural network. Due to modifications and enhancements of the AlphaZero-like training process, self-play with a only few strong GPUs of between one and several days is sufficient to reach somewhere in the range of strong-kyu up to mid-dan strength on the full 19x19 board. =Selected Publications=
 * David J. Wu (2011). Move Ranking and Evaluation in the Game of Arimaa. B.Sc. thesis, Harvard College, Cambridge, Massachusetts, pdf
 * David J. Wu (2015). Designing a Winning Arimaa Program. ICGA Journal, Vol. 38, No. 1, pdf
 * David J. Wu (2019). Accelerating Self-Play Learning in Go. arXiv:1902.10565

=Postings=
 * Neural nets for Go - chain pooling? by David Wu, Computer Go Archive, August 18, 2017

=External Links=
 * lightvector · GitHub
 * Arimaa: Game Over? by Andy Lewis, Kingpin Chess Magazine, July 11, 2015
 * Arimaa - David J. Wu - Google Play

=References= Up one level