Self-Explanatory Simulations: Scaling Up to Large Models

Proceedings of the AAAI Conference on Artificial Intelligence, 10

Volume

Representation and Reasoning

Representation and Reasoning: Qualitative

Qualitative reasoners have been hamstrung by the inability to analyze large models. This includes self-explanatory simulators, which tightly integrate qualitative and numerical models to provide both precision and explanatory power. While they have important potential applications in training, instruction, and conceptual design, a critical step towards realizing this potential is the ability to build simulators for medium-sized systems (i.e., on the order of ten to twenty independent parameters). This paper describes a new method for developing self-explanatory simulators which scales up. While our method involves qualitative analysis, it does not rely on envisioning or any other form of qualitative simulation. We describe the results of an implemented system which uses this method, and analyze its limitations and potential.