An Integrated Framework for Extended Discovery in Particle Physics
DS '01 Proceedings of the 4th International Conference on Discovery Science
Mind change efficient learning
Information and Computation
Simultaneous discovery of conservation laws and hidden particles with Smith matrix decomposition
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Mind change efficient learning
Information and Computation
Scientific model-building as search in matrix spaces
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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
| Hi-index | 0.00 |
Kocabas (1991) describes a situation from particle physics in which quantum properties and conservation laws are postulated from lists of observed and unobserved reactions. Kocabas also presents a program named BR-3 that can rediscover some accepted quantum properties from textbook data, although it fails on a more difficult example from the same source. This paper describes PAULI, a program that solves the same task as BR-3 but uses a different problem-solving model. PAULI produces different, simpler solutions than does BR-3, and it can also handle the problematic example. After comparing the two programs, we conclude that PAULI offers distinct advantages over its predecessor, which we attribute to an algebraic approach to reasoning about sets of reactions.