An important issue in computer science is research on parallel algorithms. The problems attacked with these algorithms are widespread. The author restricts himself to problems that can be represented by sets of relations on sets of variables. In artificial intelligence (AI), these problems are often called constraint satisfaction problems. Algorithms for solving constraint satisfaction problems, i.e., for finding one, several, or all solutions for a set of relations (constraints) on a set of variables, have been introduced in many AI papers. The author illustrates how connectionist networks for constraint satisfaction can be implemented. The idea is to use a connectionist node for each value of each variable and for each tuple of each constraint of the constraint satisfaction problem, and to connect them according to the way in which the constraints are related to the variables.
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