Natural languages typically permit more than one order of words or phrases, though they differ with respect to both the amount of order variation allowed and the kind of information carried by these differences in order.
Partially free word order as it occurs in German and probably to some extent in all natural languages arises through the interaction of potentially conflicting ordering principles.
In this paper, a framework for investigating conversation, which for convenience will be called the Planning Approach, is developed from this hypothesis.
In the natural-language-processing research community, the usefulness of computer tools for testing linquistic analyses is often taken for granted. Linguists, on the other hand, have generally been unaware of or ambivalent about such devices.
A primary motivation for reasoning under uncertainty is to derive decisions in the face of inconclusive evidence. Shafer’s theory of belief functions, which explicitly represents the underconstrained nature of many reasoning problems, lacks a formal procedure for making decisions.
The development of reasoning systems that can reason and plan in a continuously changing environment is emerging as an important area of research in Artificial Intelligence.
This paper presents some programming facilities for modeling the semantics of a task domain and for describing the situations that occur in that domain as a task is being carried out.
The deductive approach is a formal program construction method in which the derivation of a program from a given specification is regarded as a theorem-proving task.
