We describe two Go programs, OLGA and OLEG, developed by a Monte-Carlo approach that is simpler than Bruegmann's (1993) approach. Our method is based on Abramson (1990). We performed experiments,to assess ideas on (1) progressive pruning, (2) all moves as first heuristic, (3) temperature, (4) simulated annealing, and (5) depth-two tree search within the Monte-Carlo framework. Progressive pruning and the all moves as first heuristic are good speed-up enhancements that do not deteriorate the level of the program too much. Then, using a constant temperature is an adequate and simple heuristic that is about as good as simulated annealing. The depth-two heuristic gives deceptive results at the moment. The results of our Monte-Carlo programs against knowledge-based programs on 9x9 boards are promising. Finally, the ever-increasing power of computers lead us to think that Monte-Carlo approaches are worth considering for computer Go in the future.
We present a new method for taking advantage of the relative independence between parts of a single-player game. We describe an implementation for improving the search in a solitaire card game called Gaps. Considering the basic techniques, we show that a simple variant of Gaps can be solved by a straightforward depth-first search (DFS); tuming to variants with a larger search space, we give an approximation of the winning chances using iterative sampling. Our new method was designed to make a complete search; it improves on DFS by grouping severa! positions in a block, and searching only on the boundaries of the blocks. A block is defined as a product of independent sequences. We describe precisely how to detect interactions between sequences and how to deal with them. The resulting algorithm may run ten times faster than DFS, depending on the degree of independence between the subgames.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.