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The goal of game generation, as shown in Figure 4, is to produce a wide variety of games, all of which fall in the same class of games as described by a grammar. We also want to be able to modify the distribution of games generated by changing parameters, often in the form of probabilities. Finally, the combination of grammar and probabilities may not be enough to constrain the class according to our needs, in which case the generator should be able to handle a set of constraints.
The game generator for this class of games
is illustrated schematically in Figure 4.
The generator begins by generating a board and a set of piece names, and then generates goals and definitions for the pieces subject to the grammar and constraints, making choices using probabilities (parameters) attached to each choice-point in the grammar. Details of the generator, its parameters, and example generated games are provided in [\protect\citenamePell, 1992b].
With the provision of the class definition and generator (as well as various communications protocols to enable communication between programs, also discussed in [\protect\citenamePell, 1992b]), the problem of Metagame in symmetric chess-like games is thus fully defined. The rest of this paper is organised as follows. Section 2 discusses the challenge of representing knowledge for unknown games and the construction of METAGAMER. Section 3 discusses the analysis performed by METAGAMER to determine piece values for the games of chess and checkers, when presented with only the rules of those games, and compares this to previous work on automatic methods for determining feature values in games. Finally, Section 4 presents the results of preliminary evaluations of METAGAMER on the games of chess and checkers.