Analysis of Multi-Interpretable Ecological Monitoring Information

In this paper logical techniques developed to formalize the analysis of multi-interpretable information, in particular belief set operators and selection operators, are applied to an ecological domain. A knowledge-based decision support system is described that determines the abiotic (chemical and physical) characteristics of a site on the basis of samples of plant species that are observed. The logical foundation of this system is described in terms of a belief set operator and a selection operator. Moreover, it is shown how the belief set operator that corresponds to the system can be represented by a normal default theory.