The Meta-DENDRAL program is a vehicle for studying problems of theory formation in science. The general strategy of Meta-DENDRAL is to reason from data to plausible generalizations and then to organize the generalizations into a unified theory. Three main subproblems are discussed: Explain the experimental data for each individual chemical structure; Generalize the results from each structure to all structures; Organize the generalizations into a unified theory. The program is built upon the concepts and programmed routines already available in the Heuristic DENDRAL performance program, but goes beyond the performance program in attempting to formulate the theory which the performance program will use. (Author).

An important class of problems for which artificial intelligence methods are not well codified is constraint satisfaction. Bruce Buchanan describes Stanford's PROTEAN project which focused on a spatial constraint satisfaction problem in which determining three-dimensional spatial positions of atoms in a protein structure is the goal. Constraints are partly numerical and partly symbolic and those inferred from the data may not be satisfiable together. A blackboard model of reasoning, implemented in the BB1 framework, is used in PROTEAN.