The Test Incorporation Hypothesis and the Weak

Test incorporations are program transformations that improve the performance of generate-and-test procedures by moving information out of the \test" and into the \generator." The test information is said to be \incorporated" into the generator so that items produced by the generator are guaranteed to satisfy the incorporated test. This article proposes and investigates the hypothesis that a general theory of AI methods can be constructed using only test incorporations. Starting from an initial generate-and-test algorithm, we attempt to derive the weak methods of heuristic search, hill climbing, and avoiding duplicates via a series of test incorporations. The derivations show that test incorporations are very powerful but that occasionally other program reformulations are required. Nevertheless, we conclude that test incorporation provides a good foundation upon which to construct a general theory of methods. a The authors have chosen to list their names in alphabetical order.