Buchanan BG and Feigenbaum EA, 1978. “Dendral and Meta-Dentral: their application dimension” Artificial Intelligence115–24.

Buchanan BG, Smith DH, White WC, Gritter R, Feigenbaum EA, Lederberg J and Djerassi C, 1976. “Applications of artificial intelligence for chemical inference. XXII. Automatic rule formation in mass spectrometry by means of the meta-DENDRAL program” Journal of the American Chemical Society96 (6168).

Davies PCW, 1985. The forces of Nature (2nd ed), Cambridge University Press, Cambridge.

de Kleer JR, 1986. “An assumption-based TMS” Artificial Intelligence8127–162.

Dietterich TG and Michalski RS, 1983. “A comparative view of selected methods for learning from examples”. In: Michalski RS, Carbonell JS and Mitchell TM, eds., Machine Learning: An artificial intelligence approachMorgan Kaufmann, Los Altos, CA.

Forbus KD, 1984. “Qualitative process theory” Artificial Intelligence2485–168.

Friedland P, 1979. “Knowledge-based experiment design in molecular genetics” Proceedings Sixth International Joint Conference on Artificial Intelligence285–287.

Holmes FL, 1980. “Hans Krebs and the discovery of the Ornithine Cycle” Federation Proceedings39216–225.

Jones R, 1986. “Generating predictions to aid scientific discovery process” Proceedings Fifth National Conference on Artificial Intelligence513–516.

Karp PD, 1990. “Hypothesis formation as design”. In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.

Kocabas S, 1989. Functional categorization of knowledge: Applications in modeling scientific research and discovery PhD Thesis, Department of Electronic and Electrical Engineering, King's College London, University of London.

Kocabas S, 1991a. “Conflict resolution as discovery in particle physics” Machine Learning6277–309.

Kocabas S, 1991b. “Homuncular learning and rule parallelism: An application to BACON” Proceedings International Conference on Control950–954, IEE Conference Publications,London.

Kuhn TS, 1970. The Structure of Scientific RevolutionsUniversity of Chicago Press, Chicago, 16.

Kulkarni D, 1989. The processes of scientific research: The strategy of experimentation Doctoral Dissertation. Department of Computer Science. Carnegie Mellon University, Pittsburgh, PA.

Kulkarni D and Simon HA, 1988. “The processes of scientific discovery” Cognitive Science12139–175.

Kulkarni D and Simon HA, 1990. “The processes of scientific discovery” In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.

Langley P, 1978. “BACON1: A general discovery system” In: Proceedings Second National Conference of the Canadian Society for Computational Studies.

Langley P, Simon HA, Bradshaw GL and Zytkow JM, 1987. Scientific discovery: Computational explorations of the creative processesThe MIT Press, Cambridge, MA.

Lenat DB, 1979. “On automated scientific theory formation: a case study using the AM program” In: Hayes J, Michie D and Mikulich LI, eds., Machine Intelligence9251–283, Halstead, New York.

Lenat DB, 1983a. “The role of heuristics in learning by discovery: three case studies” In: Michalski RS, Carbonell JG and Mitchell TM, eds., Machine Learning: An artificial intelligence approachMorgan Kaufmann, Los Altos, CA.

Lenat DB, 1983b. “EURISKO: a program that learns new heuristics and domain concepts” Artificial Intelligence21 (1–2) 61–98.

Lenat DB, 1983c. “The role of heuristics in learning by discovery: three case studies” In: Michalski RS, Carbonell JC and Mitchell TM, eds., Machine Learning: An artificial intelligence approach. Morgan Kaufmann, Los Altos, CA.

Lenat DB, Prakash M and Shepherd M, 1986. “CYC: using common sense knowledge to overcome brittleness and knowledge acquisition bottlenecks” The AI Magazine7 (4) 65–85.

Lenat DB and Feigenbaum EA, 1987. “On the thresholds of knowledge” Proceedings Tenth International Joint Conference on Artificial Intelligence. 1173–1182.

Lenat DB and Guha RV1989. Building large knowledge based systems: Representation and inference in the CYC projectAddison Wesley, Reading, MA.

Michalski RS, 1983. “A theory and methodology of inductive learning” In Michalski RS, Carbonell JG and Mitchell TM, eds., Machine learning: An artificial intelligence approachMorgan Kaufmann, Los Altos, CA.

Michalski RS, 1986. “Understanding the nature of learning: issues and research directions” In: Michalski RS, Carbonell JG and Mitchell TM, eds., Machine LearningMorgan Kaufmann, Los Altos, CA.

Nilsson NJ, 1965. Learning Machines: Foundations of trainable pattern-classifying systemsMcGraw-Hill, New York, NY.

Nordhausen B and Langley P, 1990. “An integrated approach to empirical discovery” In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.

Nordhausen B and Langley P, 1987. “Towards an integrated discovery system” Proceedings Tenth International Joint Conference on Artificial Intelligence198–200.

Omnes R, 1970. Introduction to particle physics (Translated by Barton G) Wiley Interscience, London.

O'Rorke P, Morris S and Schulenburg D, 1990. “Theory formation by abstraction” In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.

Rajamoney SA, 1990. “A computational approach to theory revision” In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.

Ritchie GD and Hanna FK, 1984. “AM: a case study in AI methodology” Artificial Intelligence23249–269.

Rose D and Langley P, 1986. “Chemical discovery as belief revision” Machine Learning1423–452.

Rose D and Langley P, 1988. “A hill-climbing approach to machine discovery” Proceedings Fifth International Conference on Machine Learning367–373. Morgan Kaufmann,Ann Arbor, MI.

Shrager J and Langley P, 1990. “Computational approaches to scientific discovery” In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.

Simon HA and Lea G, 1974. “Problem solving and rule induction: A unified view” In: Gregg L, ed., Knowledge and cognition Erlbaum, Hillsdale, NJ.

Stefik M, 1978. “Inferring DNA structures from segmentation data” Artificial Intelligence1185–114.

Stefik M, 1981a. “Planning with constraints (MOLGEN: Part 1)” Artificial Intelligence2111–139.

Stefik M, 1981b. “Planning and meta-planning (MOLGEN: Part 2)” Artificial Intelligence2141–169.

Thagard P, 1988. Computational philosophy of scienceThe MIT Press, Cambridge, MA.

Thagard P, and Holyoak K, 1985. “Discovering the wave theory of sound: Inductive inference in the context of problem solving” Proceedings Ninth International Joint Conference on Artificial Intelligence610–612.

Thagard P and Nowak G, 1990. “The conceptual structure of the geological revolution” In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.

Tweney RD, 1990. “Five questions for computationalists” In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.

Zytkow JM and Simon HA, 1986. “A theory of historical discovery: the construction of componential models” Machine Learning1107–137.

Zytkow JM, 1990. “Deriving laws through analysis of processes and equations” In: Shrager J and Langley P, eds., Computational models of scientific discovery and theory formationMorgan Kaufmann, San Mateo, CA.