Michael Buro

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Michael Buro, a German computer scientist, AI-researcher, and professor at the Department of Computing Science at University of Alberta. Michael Buro is creator of the ProbCut selective extension of the alpha-beta algorithm, applied to his Othello program Logistello as part of his Ph.D. thesis at Paderborn University. In 1997, Logistello won 6-0 from the then Othello World champion Takeshi Murakami.

=GLEM= Michael Buro's General Linear Evaluation Model (GLEM), introduced at the Computer and Games 1998 conference in Tsukuba, Japan, also applied to Othello, covers not only automated tuning quite similar to Texel's Tuning Method which popularized logistic regression tuning in computer chess some years later, but further provides a procedure for exploring the feature space able to discover new evaluation features in a computational feasible way.

=Selected Publication=

1990 ...

 * Michael Buro (1990). A contribution to the determination of Rado's Sigma - or - How to catch busy beavers? Diploma thesis, RWTH Aachen (German)
 * Michael Buro (1993).  On the Maximum Length of Huffman Codes. Information Processing Letters, Vol. 45
 * Michael Buro (1994). Techniken für die Bewertung von Spielsituationen anhand von Beispielen. Ph.D. thesis. Paderborn University (German)

1995 ...

 * Michael Buro (1995). Statistical Feature Combination for the Evaluation of Game Positions. JAIR, Vol. 3
 * Michael Buro (1995). ProbCut: An Effective Selective Extension of the Alpha-Beta Algorithm. ICCA Journal, Vol 18, No. 2, pdf
 * Michael Buro (1997). An Evaluation Function for Othello Based on Statistics. NEC Research Institute. Technical Report #31.
 * Michael Buro (1997). Experiments with Multi-ProbCut and a New High-quality Evaluation Function for Othello. Technical Report No. 96, NEC Research Institute, pdf
 * Michael Buro (1997). The Othello match of the year: Takeshi Murakami vs Logistello. ICCA Journal, Vol 20, No. 3, pdf
 * Michael Buro (1998). From Simple Features to Sophisticated Evaluation Functions. CG 1998, pdf
 * Michael Buro (1999). Toward Opening Book Learning. ICCA Journal, Vol 22, No. 2, pdf » Book Learning
 * Michael Buro (1999). Efficient Approximation of Backgammon Race Equities. ICCA Journal, Vol 22, No. 3, also published (2000) in Games in AI Research, pdf

2000 ...

 * Michael Buro (2000). Experiments with Multi-ProbCut and a new High-Quality Evaluation Function for Othello. Games in AI Research, pdf
 * Michael Buro (2000). Toward Opening Book Learning. Games in AI Research, pdf
 * Michael Buro (2000). Simple Amazons Endgames and Their Connection to Hamilton Circuits in Cubic Subgrid Graphs. CG 2000, pdf
 * Michael Buro (2001). Efficient Approximation of Backgammon Race Equities. Advances in Computer Games 9
 * Michael Buro, Igor Durdanovic (2001). An Overview of NECI’s Generic Game Server. 6th Computer Olympiad Workshop, pdf
 * Michael Buro (2002). Improving Mini-max Search by Supervised Learning. Artificial Intelligence, Vol. 134, No. 1
 * Michael Buro (2002). Report on the IWEC-2002 Man-Machine Othello Match. ICGA Journal, Vol. 25, No. 2, pdf
 * Michael Buro (2002). ORTS: A Hack-Free RTS Game Environment. CG 2002, pdf
 * Dave Gomboc, Tony Marsland, Michael Buro (2003). Evaluation Function Tuning via Ordinal Correlation. University of Alberta, Edmonton, Alberta, Canada, Advances in Computer Games 10, pdf
 * Michael Buro (2003). The Evolution of Strong Othello Programs. IFIP, Vol. 112, Springer
 * Albert Xin Jiang, Michael Buro (2003). First Experimental Results of ProbCut Applied to Chess. Advances in Computer Games 10, pdf
 * Thomas Hauk, Michael Buro, Jonathan Schaeffer (2004). Rediscovering *-Minimax Search. CG 2004, pdf
 * Thomas Hauk, Michael Buro, Jonathan Schaeffer (2004). *-Minimax Performance in Backgammon. CG 2004

2005 ...

 * Dave Gomboc, Michael Buro, Tony Marsland (2005). Tuning evaluation functions by maximizing concordance Theoretical Computer Science, Vol. 349, No. 2, pdf
 * Frantisek Sailer, Michael Buro, Marc Lanctot (2007). Adversarial planning through strategy simulation. CIG 2007, pdf
 * Timothy Furtak, Michael Buro (2009). Minimum Proof Graphs and Fastest-Cut-First Search Heuristics. IJCAI 2009, pdf

2010 ...

 * Jeffrey Long, Nathan Sturtevant, Michael Buro, Timothy Furtak (2010). Understanding the Success of Perfect Information Monte Carlo Sampling in Game Tree Search. AAAI 2010, pdf
 * Timothy Furtak, Michael Buro (2011). Using Payoff-Similarity to Speed Up Search. IJCAI 2011, pdf » Skat, Transposition Table
 * Abdallah Saffidine, Hilmar Finnsson, Michael Buro (2012). Alpha-Beta Pruning for Games with Simultaneous Moves. AAAI 2012
 * Timothy Furtak, Michael Buro (2013). Recursive Monte Carlo search for imperfect information games. CIG 2013, pdf
 * Adi Botea, Bruno Bouzy, Michael Buro, Christian Bauckhage, Dana S. Nau (2013). Pathfinding in Games. Artificial and Computational Intelligence in Games 2013, pdf
 * Peter Cowling, Michael Buro, Michal Bída, Adi Botea, Bruno Bouzy, Martin V. Butz, Philip Hingston, Hector Muñoz-Avila, Dana S. Nau, Moshe Sipper (2013). Search in Real-Time Video Games. Artificial and Computational Intelligence in Games 2013, pdf

=External Links=
 * Michael Buro's homepage
 * Michael Buro - Faculty of Science UoA
 * Michael Buro – Google+
 * Photo Gallery: Friends and Peers by Darse Billings

=References=

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