Learning Qualitative Models of Physical and Biological Systems

Authors:
Simon M. Garrett;George M. Coghill;Ashwin Srinivasan;Ross D. King
Affiliations:
Department of Computer Science, University of Wales, Aberystwyth, United Kingdom;Department of Computing Science, University of Aberdeen, Aberdeen, United Kingdom;Computing Laboratory, Oxford University, Oxford, United Kingdom;Department of Computer Science, University of Wales, Aberystwyth, United Kingdom
Venue:
Computational Discovery of Scientific Knowledge
Year:
2007

Citing 22
Cited 1

Qualitative process theory

Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Qualitative simulation

Artificial Intelligence
Causality in device behavior

Artificial Intelligence
Qualitative physics using dimensional analysis

Artificial Intelligence
Dynamic across-time measurement interpretation

Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Genetic programming (videotape): the movie

Genetic programming (videotape): the movie
Automated Refinement of First-Order Horn-Clause Domain Theories

Machine Learning
Metamodelling: for bond graphs and dynamic systems

Metamodelling: for bond graphs and dynamic systems
Qualitative system identification: deriving structure from behavior

Artificial Intelligence
Theories for mutagenicity: a study in first-order and feature-based induction

Artificial Intelligence - Special volume on empirical methods
Learning Qualitative Models of Dynamic Systems

Machine Learning - special issue on inductive logic programming
System identification (2nd ed.): theory for the user

System identification (2nd ed.): theory for the user
Revising the logical foundations of inductive logic programming systems with ground reduced programs

New Generation Computing - Special issue on inductive logic programming 97
Separate-and-Conquer Rule Learning

Artificial Intelligence Review
Continuous System Modeling

Continuous System Modeling
Practical Guide to Computer Methods for Engineers

Practical Guide to Computer Methods for Engineers
Inductive Logic Programming: Techniques and Applications

Inductive Logic Programming: Techniques and Applications
Feature construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity Aided by Structural Attributes

Data Mining and Knowledge Discovery
Chunking in Soar: The Anatomy of a General Learning Mechanism

Machine Learning
Declarative Bias in Equation Discovery

ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Learning from Positive Data

ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
Version spaces: an approach to concept learning.

Version spaces: an approach to concept learning.

Inductive process modeling

Machine Learning

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a qualitative model-learning system, Qoph, developed for application to scientific discovery problems. Qophlearns the structuralrelations between a set of observed variables. It has been shown capable of learning models with intermediate (unmeasured) variables, and intermediate relations, under different levels of noise, and from qualitative or quantitative data. A biological application of Qophis explored. An additional significant outcome of this work is the discovery and identification of kernel subsets of key states that must be present for model-learning to succeed.