Bruno Bouzy: Associating Shallow and Selective Global Tree Search with Monte Carlo for 9*9 Go. Computers and Games Bruno Bouzy of Paris Descartes, CPSC, Paris (Paris 5) with expertise in: Artificial Intelligence. Read 73 publications, and contact Bruno Bouzy on ResearchGate. Bruno Bouzy is a player and programmer from France. Born in , his highest rank was 3 dan. He was vice champion of France, losing in the.

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Experiments Starting from the basic idea, this section describes the various enhancements with their effect on the level of go programs: Artificial Intelligencepages — The move decision process of indigo.

Given the great number of problems and the diversity of possible solutions, Computer Go is an attractive research domain for AI. The maximal threshold is fixed to 10, multiplied by the number of legal moves. This module can be either a vouzy or a bouzh to Monte Carlo.

Wednesday, April 9, – 1: However, we will see that it is possible both, to fix the temperature to a constant value, and even to make it infinite, which means that all moves are played with equal probability. Compared to the very slow basic idea, the gain in speed is important. Section 3 focusses on the main ideas underlying our work.

This phenomenon happens when captures have already occurred at the time when the move is played. To a large extent, this is probably due to the different definitions of an eye used in both programs, and also to the fact that Oleg does some post-processing to avoid playing somewhere if the stone can be captured in a ladder.


The motivation for using simulated annealing was probably that the program would gain some reading ability, but bpuzy have not seen any evidence of this, the program making the same kind of tactical blunders. Oleg takes a long time to play about 3 hours per game for several reasons. It is based on the same ideas as Gobble; particularly it uses simulated annealing.

CiteSeerX — Computer Go: an AI Oriented Survey

Some of our experiments with Oleg constitutes the basis of our discussion. It might be possible to link the value of a move to more local subgoals from which we could establish statistics.

The game of the Amazons is a quite new game whose rules stand bohzy the game of Go and Chess. On a 2 Ghz computer, Olga plays 7, random 9×9 games per second and Oleg 10, The validity of the tactical results would depend on the moves already played and it would be difficult to build an accurate mechanism this end.

Nowadays, some programs are better than human players in most classical games. Its move decision process is described in [Bouzy, ].

To evaluate a position, play a given number of completely random games to the end – without filling the eyes – and score them. In figure 3 the point C is good for white and bad for black.


Information Sciences, pages — This idea constitutes the cornerstone of our work. Static analysis of life and death in the game of go. On one hand, mathematical morphology is a very powerful tool within image processing community. Prospective methods of programming the game of Go will probably be of interest in other domains as well. Finally, it is still slower than classical programs and it is difficult to make them play on boards larger than 13x Optimization by simulated annealing.

We have set up experiments to assess ideas such as progressive pruning, transpositions, temperature, simulated annealing and depth-two tree search within the Monte Carlo framework. On the other … More. Thus, it uses about 2 hours per 9×9 game, which yields results in a reasonable time. Our Work First, this section describes the basic idea underlying our work.

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On the contrary D and E are good for black only. Progressive pruning does not need transpositions, temperature or simulated annealing.

However, optimizing the program very roughly is important. Game-tree searching by min-max approximation.