2 research outputs found
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The test incorporation hypothesis and the weak methods
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
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Learning at the knowledge level
When Newell introduced the concept of the knowledge level as a useful level of description for computer systems, he focused on the representation of knowledge. This paper applies the knowledge level notion to the problem of knowledge acquisition. Two interesting issues arise. First, some existing machine learning programs appear to be completely static when viewed at the knowledge level. These programs improve their performance without changing their "knowledge." Second, the behavior of some other machine learning programs cannot be predicted or described at the knowledge level. These programs take unjustified inductive leaps. The first programs are called symbol level learning (SLL) programs; the second, .non-deductive knowledge level learning (NKLL) programs. The paper analyzes both of these classes of learning programs and speculates on the possibility of developing coherent theories of each. A theory of symbol level learning is sketched, and some reasons are presented for believing that a theory of NKLL will be difficult to obtain