ACM Transactions on Programming Languages and Systems (TOPLAS)
Multifacetted modelling and discrete event simulation
Multifacetted modelling and discrete event simulation
The use of aggregation in causal simulation
Artificial Intelligence
Role of process abstraction in simulation
IEEE Transactions on Systems, Man and Cybernetics
Compositional modeling: finding the right model for the job
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
A multimodel methodology for qualitative model engineering
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Reasoning about model accuracy
Artificial Intelligence
AI: what simulationists really need to know
ACM Transactions on Modeling and Computer Simulation (TOMACS)
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A logic-based foundation of discrete event modeling and simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Qualitative reasoning: modeling and simulation with incomplete knowledge
Qualitative reasoning: modeling and simulation with incomplete knowledge
Metamodeling: a state of the art review
WSC '94 Proceedings of the 26th conference on Winter simulation
Automated modeling for answering prediction questions: selecting the time scale and system boundary
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Theory of Modelling and Simulation
Theory of Modelling and Simulation
Assessment of simulation models based on trace-file analysis: a metamodeling approach
Proceedings of the 30th conference on Winter simulation
On simulation model complexity
Proceedings of the 32nd conference on Winter simulation
Reduced discrete-event simulation models for medium-term production scheduling
Systems Analysis Modelling Simulation
Do we need metamodels AND ontologies for engineering platforms?
Proceedings of the 2006 international workshop on Global integrated model management
A framework for configurable hierarchical simulation in a multiple-user decision support environment
WSC '05 Proceedings of the 37th conference on Winter simulation
Proceedings of the 40th Conference on Winter Simulation
Verifying trace inclusion between an experimental frame and a model
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Multilayer perceptron for simulation models reduction: Application to a sawmill workshop
Engineering Applications of Artificial Intelligence
Models within models: taming model complexity using the sub-model lattice
FASE'11/ETAPS'11 Proceedings of the 14th international conference on Fundamental approaches to software engineering: part of the joint European conferences on theory and practice of software
Controlled simplification of material flow simulation models
Winter Simulation Conference
Reducing software architecture models complexity: a slicing and abstraction approach
FORTE'06 Proceedings of the 26th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems
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Model abstraction is a method for reducing the complexity of a simulation model while maintaining the validity of the simulation results with respect to the question that the simulation is being used to address. Model developers have traditionally used a number of abstraction techniques, and simulation researchers have conducted formal research to build a theoretical foundation for model manipulation. More recently, researchers in the artificial intelligence (AI) subfield of qualitative simulation have also been developing techniques for simplifying models, determining whether models results are valid, and developing tools for automatic model selection and manipulation. Metamodeling can also be considered as an abstraction technique. The purpose of the paper is to provide a taxonomy of abstraction techniques drawn from these fields. This taxonomy provides a framework for comparing and contrasting various abstraction techniques.