WorldCat Identities

Müller, Martin 1965-

Overview
Works: 3 works in 24 publications in 1 language and 364 library holdings
Genres: Conference papers and proceedings 
Roles: Editor, Author, 958, Opponent
Publication Timeline
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Most widely held works by Martin Müller
Computers and games : third international conference, CG 2002, Edmonton, Canada, July 25-27, 2002 : revised papers by Jonathan Schaeffer( Book )

14 editions published in 2003 in English and held by 220 WorldCat member libraries worldwide

This book constitutes the thoroughly refereed post-proceedings of the Third International Conference on Computers and Games, CG 2002, held in Edmonton, Alberta, Canada in July 2002. The 27 revised full papers presented were carefully selected during two rounds of reviewing and improvement. The papers are organized in topical sections on evaluation and learning, search, combinatorial games and theory opening and endgame databases, single-agent search and planning, and computer Go
Computer go as a sum of local games : an application of combinatorial game theory by Martin Müller( Book )

9 editions published in 1995 in English and Undetermined and held by 13 WorldCat member libraries worldwide

Introduction of statistics in optimization by Fabien Teytaud( )

1 edition published in 2011 in English and held by 1 WorldCat member library worldwide

In this thesis we study two optimization fields. In a first part, we study the use of evolutionary algorithms for solving derivative-free optimization problems in continuous space. In a second part we are interested in multistage optimization. In that case, we have to make decisions in a discrete environment with finite horizon and a large number of states. In this part we use in particular Monte-Carlo Tree Search algorithms. In the first part, we work on evolutionary algorithms in a parallel context, when a large number of processors are available. We start by presenting some state of the art evolutionary algorithms, and then, show that these algorithms are not well designed for parallel optimization. Because these algorithms are population based, they should be we well suitable for parallelization, but the experiments show that the results are far from the theoretical bounds. In order to solve this discrepancy, we propose some rules (such as a new selection ratio or a faster decrease of the step-size) to improve the evolutionary algorithms. Experiments are done on some evolutionary algorithms and show that these algorithms reach the theoretical speedup with the help of these new rules.Concerning the work on multistage optimization, we start by presenting some of the state of the art algorithms (Min-Max, Alpha-Beta, Monte-Carlo Tree Search, Nested Monte-Carlo). After that, we show the generality of the Monte-Carlo Tree Search algorithm by successfully applying it to the game of Havannah. The application has been a real success, because today, every Havannah program uses Monte-Carlo Tree Search algorithms instead of the classical Alpha-Beta. Next, we study more precisely the Monte-Carlo part of the Monte-Carlo Tree Search algorithm. 3 generic rules are proposed in order to improve this Monte-Carlo policy. Experiments are done in order to show the efficiency of these rules
 
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Audience Level
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Audience level: 0.71 (from 0.70 for Computers ... to 0.99 for Introducti ...)

Computers and games : third international conference, CG 2002, Edmonton, Canada, July 25-27, 2002 : revised papers
Languages
English (23)

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