Taxonomy, Structure, and Implementation of Evidential Reasoning
This work addresses evidential reasoning for military situation assessment, but it is incremental as it builds on existing tools like Bayesian networks without introducing major new methods.
The paper tackles the problem of representing and solving evidential reasoning problems by describing fundamental elements and structures, using Bayesian inference networks and state space formalism, and illustrating a human-oriented decision-making cycle for military situation assessment. The result is an implementation that serves as a basis for an expert system shell, specifically a situation assessment processor.
The fundamental elements of evidential reasoning problems are described, followed by a discussion of the structure of various types of problems. Bayesian inference networks and state space formalism are used as the tool for problem representation. A human-oriented decision making cycle for solving evidential reasoning problems is described and illustrated for a military situation assessment problem. The implementation of this cycle may serve as the basis for an expert system shell for evidential reasoning; i.e. a situation assessment processor.