QCM: A QP-based concept map system
Morteza Dehghani, Kenneth D. Forbus · 2009
Qualitative representations have proven to be useful formalisms for capturing human mental models. As a result, qualitative modeling could become an important tool for cognitive science. Specifically, an environment in which qualitative representations can be used to explore mental models and different type of reasoning and simulations can be performed on these models can be a useful tool for cognitive scientists. In this paper, we introduce the Qualitative Concept Map system, designed for cognitive scientists, for building and simulating qualitative and Bayesian models using qualitative process theory and Bayesian inference. in several ways. First, we integrated our qualitative simulator (Gizmo), to provide a complementary firstprinciples simulation engine. Second, we added a probabilistic reasoning mode. Finally, we enhanced the user interface functionality to provide easier access to reasoning features. We first introduce our system, discuss its different features and describe some real-world cognitive science examples modeled in it. Next, we describe the qualitative mode of the system and Gizmo. We then describe the probabilistic mode and how information available in the qualitative mode can be integrated into the probabilistic mode. We close by discussing related and future work.