Abstract
MEDICUS2 is an Intelligent Problem Solving Environment (IPSE) currently under development. It is designed to support i) the construction of explanation models, and ii) the training of diagnostic reasoning and hypotheses testing in domains of complex, fragile, and uncertain knowledge. MEDICUS is currently developed and applied in the epidemiological fields of environmentally caused diseases and human genetics. Uncertainty is handled by the Bayesian network approach. Thus the modelling task for the learner consists of creating a Bayesian network for the problem at hand. He / she may test hypotheses about the model, and the system provides help. This differs from existing reasoning systems based on Bayesian networks, i.e. in medical domains, which contain a built-in knowledge base that may be used but not created or modified by the learner. For supporting diagnostic reasoning, MEDICUS proposes diagnostic hypotheses and examinations. This will be extended to support learners' acquisition and training of diagnostic strategies.
We thank Karsten Rommerskirchen for assisting in the implementation and in the mathematical work
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Folckers, J., Möbus, C., Schröder, O., Thole, HJ. (1996). An intelligent problem solving environment for designing explanation models and for diagnostic reasoning in probabilistic domains. In: Frasson, C., Gauthier, G., Lesgold, A. (eds) Intelligent Tutoring Systems. ITS 1996. Lecture Notes in Computer Science, vol 1086. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61327-7_133
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