| Many complex physical systems such as biological, ecological, and other natural systems are characterized both by incomplete models and limited empirical data. Accurate prediction of the behavior of such systems requires exploitation of multiple, individually incomplete, knowledge sources.; This dissertation describes model-based adaptation, a technique for integrating case-based reasoning with model-based reasoning to predict the behavior of biological systems characterized both by incomplete causal models and insufficient empirical data for accurate induction. This approach is implemented in CARMA, a system for rangeland grasshopper management advising. CARMA implements a process model derived from protocol analysis of human expert problem-solving episodes. CARMA's design attempts to emulate the speed, graceful degradation, opportunism, and explanatory ability of human experts.; CARMA's ability to predict the forage consumption judgements of expert entomologists was empirically compared to that of case-based and model-based reasoning techniques in isolation. This evaluation confirmed the hypothesis that integrating model-based and case-based reasoning can lead to more accurate predictions than the use of either technique individually. |
