Artificial Intelligence
KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
C4.5: programs for machine learning
C4.5: programs for machine learning
Qualitative system identification: deriving structure from behavior
Artificial Intelligence
Learning Qualitative Models of Dynamic Systems
Machine Learning - special issue on inductive logic programming
Semi-quantitative system identification
Artificial Intelligence
Machine Learning and Data Mining; Methods and Applications
Machine Learning and Data Mining; Methods and Applications
Qualitative reverse engineering
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Control Skill, Machine Learning and Hand-crafting in Controller Design
Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995]
Skill modeling through symbolic reconstruction of operator's trajectories
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Qualitative simulation and related approaches for the analysis of dynamic systems
The Knowledge Engineering Review
The Knowledge Engineering Review
Induction of Fuzzy and Annotated Logic Programs
Inductive Logic Programming
Learning Different User Profile Annotated Rules for Fuzzy Preference Top-k Querying
SUM '07 Proceedings of the 1st international conference on Scalable Uncertainty Management
Ascending and descending regions of a discrete Morse function
Computational Geometry: Theory and Applications
Probabilistic and analytical estimation of software development team size
International Journal of Hybrid Intelligent Systems
The Knowledge Engineering Review
Learning qualitative models from numerical data
Artificial Intelligence
Learning qualitative models from numerical data: extended abstract
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In general, modeling is a complex and creative task, and building qualitative models is no exception. One way of automating this task is by means of machine learning. Observed behaviors of a modeled system are used as examples for a learning algorithm that constructs a model that is consistent with the data. In this article, we review approaches to learning qualitative models, either from numeric data or qualitative observations. We describe the QUIN program that looks for qualitative patterns in numeric data and outputs the results of learning as "qualitative trees." We illustrate this using applications associated with systems control, in particular, the identification and optimization of controllers and human operator's control skill. We also review approaches that learn models in terms of qualitative differential equations.