Modeling Heterogeneous Systems

Abstract

Reasoning practices and decision making often require information from many different sources, which can be both sentential and diagrammatic. In such situations, there are many advantages to reasoning with the diagrams themselves, as opposed to re-expressing the information content of the diagram in sentential form and reasoning in an abstract sentential language. Thus for these practices, being able to extract and re-express pieces of information from one kind of representation into another is essential. The main goal of this paper is to propose a general framework for the modeling of heterogeneous reasoning systems and, most importantly, heterogeneous rules of inference in those systems. Unlike some other work in designing heterogeneous systems, our purpose will not be to define just one notion of heterogeneous inference, but rather to provide a framework in which many different kinds of heterogeneous rules of inference can be defined. After proposing this framework, we will then show how it can be applied to a sample heterogeneous system to define a number of different heterogeneous rules of inference. We will also discuss how the framework can be used to define rules of inference similar to the Observe Rule in Barwise and Etchemendy’s Hyperproof system.