A perspective on symbolic mathematical computing and artificial intelligence
Annals of Mathematics and Artificial Intelligence
The Computer-Aided Discovery of Scientific Knowledge
DS '98 Proceedings of the First International Conference on Discovery Science
The Melting Pot of Automated Discovery: Principles for a New Science
DS '99 Proceedings of the Second International Conference on Discovery Science
Automated Formulation of Reactions and Pathways in Nuclear Astrophysics: New Results
DS '01 Proceedings of the 4th International Conference on Discovery Science
An Integrated Framework for Extended Discovery in Particle Physics
DS '01 Proceedings of the 4th International Conference on Discovery Science
Automated scientific discovery
Handbook of data mining and knowledge discovery
Mind change efficient learning
Information and Computation
Mind change efficient learning
Information and Computation
Theory-driven discovery of reaction pathways in the MECHEM system
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Scientific model-building as search in matrix spaces
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Incremental discovery of hidden structure: applications in theory of elementary particles
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Discovery of conservation laws via matrix search
DS'10 Proceedings of the 13th international conference on Discovery science
Mind change efficient learning
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Automated Discovery Of Empirical Laws
Fundamenta Informaticae
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In this paper we focus on the general problem of identifying and resolving conflicts such as inconsistency and incompleteness in scientific discovery. The underlying idea is that conflicts in empirical knowledge can lead to new discoveries, provided that they are clearly identified. Our observations are based on the behavior and the results of an incremental discovery program, BR-3. The system models the discoveries of a series of quantum laws by physicists in this century. BR-3's discoveries are directed by a small set of consistency and completeness constraints. We evaluate the system in terms of its knowledge representation, discovery operators, and their behavior, and we describe its relation to other work in scientific discovery.