Abstract:
Case-based approaches predict the behaviour of dynamic systems by analysing a given experimental setting in the context of others. To select similar cases and to control adaptation of cases, they employ general knowledge. If that is neither available nor inductively derivable, the knowledge implicit in cases can be utilized for a case-based ranking and adaptation of similar cases. We introduce the system OASES and its application to medical experimental studies to demonstrate this approach. Keywords: Case-Based Reasoning; Case-Based Similarity Ranking; Case-Based Adaptation; Prediction; Experimental Studies 1 Introduction Simulation is an experiment performed on a model that is aimed at answering questions about the behaviour of a system. The experiment we are interested in is analysing and predicting the effect of settings in experimental medical studies. The subjects of these experimental studies define the system, namely the organisms that the model is intended to represent. Mode...
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