To use language one must be able to make inferences about the information which language conveys. This is apparent in many ways. For one thing, many of the processes which we typically consider "linguistic" require inference making. For example, structural disambiguation: (1) Waiter, I would like spaghetti with meat sauce and wine. You would not expect to be served a bowl of spaghetti floating in meat sauce and wine. That is, you would expect the meal represented by structure (2) rather than that represented by (3).

This view is nominalism, and leads to a quite different sort of semantic intuition, in which, for example, red denotes not a property of physical individuals, but the (rather disconnected) individual consisting of all pieces of red stuff in the world. Other similar confusions are also made. For example, logic is no worse (and no better) than Conceptual Dependency at representing warm, human facts about people hitting each other, (4) Logic doesn't give "the ultimate in decomposition of knowledge". Winograd, in his widely cited discussion [23] of the assertional/procedural controversy, draws a distinction between logic's atomistic view of knowledge, in which a representation is seen as a set of separate disconnected facts, and the proceduralist's holistic view in which interactions between procedures have prominence. But this is exactly the opposite of the truth.

In English, "1ikewise", "too", "similarly", etc., followed optionally by a preposition and then by a noun phrase indicate that the role filled by the new noun phrase in a previously mentioned predicate is a non-subject one.

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In L. Steels (Ed.), Advances in natural language processing. Antwerp, Belgium: University of Antwerp.

Abstract: A data base system that supports natural language queries is not really natural if it requires the user to know how the data are represented. This paper defines a formalism, called conceptual graphs, that can describe data according to the user’s view and access data according to the system’s view. In addition, the graphs can represent functional dependencies in the data base and support inferences and computations that are not explicit in the initial query.IBM Journal of Research and Development 20:4, pp. 336-357.

Sentences in first-order predicate logic can be usefully interpreted as programs. In this paper the operational and fixpoint semantics of predicate logic programs are defined, and the connections with the proof theory and model theory of logic are investigated. It is concluded that operational semantics is a part of proof theory and that fixpoint semantics is a special case of model-theoretic semantics.

The first section discusses the importance of having systems that understand the concept of knowledge, and how knowledge is related to action. Section 2 points out some of the special problems that are involved in reasoning about knowledge, and section S presents a logic of knowledge based on the idea of possible worlds. Section 4 integrates this with a logic of actions and gives an example of reasoning in the combined system. Section 5 makes some concluding comments.

Fourth International Joint Conference on Artificial Intelligence Advance Papers, pp. 26B-273

The frame problem arises in attempts to formalise problem--solving processes involving interactions with a complex world. It concerns the difficulty of keeping track of the consequences of the performance of an action in, or more generally of the making of some alteration to, a representation of the world. The paper contains a survey of the problem, showing how it arises in several contexts and relating it to some traditional problems in philosophical logic. In the second part of the paper several suggested partial solutions to the problem are outlined and compared. This comparison necessitates an analysis of what is meant by a representation of a robot's environment.