Model Decomposition Based Qualitative Simulation

Qualitative reasoning uses incomplete knowledge to compute a description of the possible behaviors for dynamic systems. For standard QSIM algorithm frequently results in a large number of incomprehensible behavioral descriptions and the simulation for complex systems frequently is intractable, model decomposition methods are used to decompose the complex system model into simple sub-models. Qualitative simulation based on model decomposition uses a divide and conquer approach to simulate the whole system. Variables within the system are partitioned into components. Each component is viewed as a separate system and is simulated using a state-based representation limited to the variables within the component. Interactions between sub-models are reasoned about separately. Qualitative simulation algorithm based on model decomposition provides a promising paradigm for qualitative simulation whose complexity is driven by the complexity of the problem specification rather than the inference mechanism used.