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One way of enhancing the problem-solving power of a domain-specialised automatic problem solver is the introduction of domain-important concepts, defined as patterns, for streamlining the problem-solving process. The number of patterns needed for certain kinds of tasks, or domains, like chess, can be so high that the success of this approach to the development of powerful problem-solvers critically depends on two questions: <(a) How much programming effort is needed to implement such patterns in a programming language? (b) How efficiently, in terms of execution time, can these patterns be evaluated? In this paper several fundamentally different approaches to the implementation of problem-domain meaningful patterns, using a complex chess problem as an example, are compared. In particular, an approach based on cellular array processing operations is investigated.