for rules or strategies in a non-model-specific fashion? However, Klver applies the parameters he proposes only to his own basic model. As a result, it is impossible to tell whether those parameters, let alone their specific values, ought to be of any interest to those using other basic models. Klver does indicate that he has experimented with different models in studying some parameters (e.g. p. 149) but no specifics are given. Since all the different 'models' discussed in the book appear to be based on the same basic approach to social stratification, one suspects that these different models were simply additional variations on the same theme. In chapter four, Klver's focus turns to the parameters that affect whether systems stagnate and how they can break out of stagnation and/or overcome crises. This is obviously an issue of directed search within a specific search space and I missed a discussion of different search algorithms that would have seemed appropriate here. Genetic algorithms are discussed, and classifier systems are mentioned, but I would have liked to see a more formal treatment of their strengths and weaknesses at exploring different kinds of search spaces. Simulated annealing, another potentially valuable model, is not get considered at all. Nor is there much discussion of the nature of search spaces themselves and how they might differ for different models. Yet this is obviously a crucial issue. Some of the best work in this respect is that based on Kauffman's NK landscape model ( 1993 ), which