Equation generation for clustering
IEA/AIE '90 Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Learning Qualitative Models of Dynamic Systems
Machine Learning - special issue on inductive logic programming
Discovering admissible simultaneous equations of large scale systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Machine Learning
A Knowledge-Based Equation Discovery System for Engineering Domains
IEEE Expert: Intelligent Systems and Their Applications
Discovering Admissible Simultaneous Equation Models from Observed Data
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Toward the Discovery of First Principle Based Scientific Law Equations
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Discovery of Differential Equations from Numerical Data
DS '98 Proceedings of the First International Conference on Discovery Science
Development of SDS2: Smart Discovery System for Simultaneous Equation Systems
DS '98 Proceedings of the First International Conference on Discovery Science
Data mining tasks and methods: Equation fitting: methodology for equation fitting
Handbook of data mining and knowledge discovery
Data mining tasks and methods: Equation fitting: equation finders
Handbook of data mining and knowledge discovery
Automated scientific discovery
Handbook of data mining and knowledge discovery
Communicability Criteria of Law Equations Discovery
Computational Discovery of Scientific Knowledge
Discovering admissible models of complex systems based on scale-types and identity constraints
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Discovering interesting holes in data
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Qualitative system identification from imperfect data
Journal of Artificial Intelligence Research
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Towards an integrated discovery system
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Modelling experiments in scientific discovery
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Discovering time differential law equations containing hidden state variables and chaotic dynamics
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Critical hypersurfaces and the quantity space
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
Critical hypersurfaces and the quantity space
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
Automated discovery in a chemistry laboratory
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Discovery of equations: experimental evaluation of convergence
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Operational definition refinement: a discovery process
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Learning engineering models with the minimum description length principle
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
SCALETRACK: a system to discover dynamic law equations containing hidden states and chaos
DS'05 Proceedings of the 8th international conference on Discovery Science
Thinking through diagrams: discovery in game playing
SC'04 Proceedings of the 4th international conference on Spatial Cognition: reasoning, Action, Interaction
Automated Discovery Of Empirical Laws
Fundamenta Informaticae
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Most research on inductive learning has been concerned with qualitative learning that induces conceptual, logic-style descriptions from the given facts. In contrast, quantitative learning deals with discovering numerical laws characterizing empirical data. This research attempts to integrate both types of learning by combining newly developed heuristics for formulating equations with the previously developed concept learning method embodied in the inductive learning program AQ11. The resulting system, ABACUS, formulates equations that bind subsets of observed data, and derives explicit, logic-style descriptions stating the applicability conditions for these equations. In addition, several new techniques for quantitative learning are introduced. Units analysis reduces the search space of equations by examining the compatibility of variables' units. Proportionality graph search addresses the problem of identifying relevant variables that should enter equations. Suspension search focusses the search space through heuristic evaluation. The capabilities of ABACUS are demonstrated by several examples from physics and chemistry.