A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraint satisfaction problem (CSP). Various distributed or parallel computing approaches have been used to solve these problems. Mainly, these approaches can be classified as variable-based, domain-based, and function-based distributed problem solving strategies. Only some of the strategies used are scalable to large parallel machines while others are suitable only for small distributed platforms. The different approaches are presented and discussed.