Artificial Intelligence
Compositional modeling: finding the right model for the job
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Solution reuse in dynamic constraint satisfaction problems
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Efficient compositional modeling for generating causal explanations
Artificial Intelligence
Semiring-based constraint satisfaction and optimization
Journal of the ACM (JACM)
Automated modeling of complex systems to answer prediction questions
Artificial Intelligence
Automated model selection for simulation based on relevance reasoning
Artificial Intelligence
Solution Techniques for Constraint Satisfaction Problems: Foundations
Artificial Intelligence Review
Solution Techniques for Constraint Satisfaction Problems: Advanced Approaches
Artificial Intelligence Review
Reasoning about nonlinear system identification
Artificial Intelligence
Inducing Process Models from Continuous Data
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Declarative Bias in Equation Discovery
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Generalized Physical Networks for Automated Model Building
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
The Knowledge Engineering Review
Hard, flexible and dynamic constraint satisfaction
The Knowledge Engineering Review
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Probabilistic abductive computation of evidence collection strategies in crime investigation
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
Conditional constraint satisfaction: logical foundations and complexity
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Knowledge based crime scenario modelling
Expert Systems with Applications: An International Journal
IEEE Transactions on Fuzzy Systems
Compositional Bayesian modelling for computation of evidence collection strategies
Applied Intelligence
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The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mechanism takes a scenario describing the constituent interacting components of a system and translates it into a useful mathematical model. This paper presents a novel compositional modelling approach aimed at building model repositories. It furthers the field in two respects. Firstly, it expands the application domain of compositional modelling to systems that can not be easily described in terms of interacting functional components, such as ecological systems. Secondly, it enables the incorporation of user preferences into the model selection process. These features are achieved by casting the compositional modelling problem as an activity-based dynamic preference constraint satisfaction problem, where the dynamic constraints describe the restrictions imposed over the composition of partial models and the preferences correspond to those of the user of the automated modeller. In addition, the preference levels are represented through the use of symbolic values that differ in orders of magnitude.