Varol Akman

The success of set theory as a foundation for mathematics inspires its use in artificial intelligence, particularly in commonsense reasoning. In this survey, we briefly review classical set theory from an AI perspective, and then consider alternative set theories. Desirable properties of a possible commonsense set theory are investigated, treating different aspects like cumulative hierarchy, self-reference, cardinality, etc. Assorted examples from the ground-breaking research on the subject are also given.

P.F. Strawson proposed in the early seventies a threefold distinction regarding how context bears on the meaning of "what is said" when a sentence is uttered. The proposal was somewhat tentative and, being aware of this aspect, Strawson himself raised various questions to make it more adequate. In this paper, we review Strawson's scheme, note his concerns, and add some of our own. We also defend its essence and recommend it as an insightful entry point re the interplay of intended meaning and context.

[This is a review of: Drew McDermott, Mind and Mechanism, MIT Press, Cambridge, MA, 2001.] The author is interested in computational approaches to consciousness. His reason for working in the field of AI is to solve the mind-body problem, that is, to understand how the brain can have experiences. This is an intricate project because it involves elucidation of the relationship between our mentality and its physical foundation. How can a biological/chemical system (the human body) have experiences, beliefs, desires, intentions, and so on? Physicists have good reasons to persuade us that ours is a material world that obeys physical laws. Once we commit ourselves to this view, it sounds quite bewildering to think that there is a place for independently existing minds in such a world. When physicists speak, McDermott listens. His hypothesis is that we are all contraptions designed by evolution. The concept of mind arises because people’s brains are biological computers. Crudely put, minds are produced by brains. The essential contribution of this rich book is an extended argument about how one can be more specific about the way this production is realized.

While situation theory and situation semantics provide an appropriate framework for a realistic model-theoretic treatment of natural language, serious thinking on their 'computational' aspects has just started. Existing proposals mainly offer a Prolog- or Lisp-like programming environment with varying degrees of divergence from the ontology of situation theory. In this paper, we introduce a computational medium (called BABY-SIT) based on situations. The primary motivation underlying BABY-SIT is to facilitate the development and testing of programs in domains ranging from linguistics to artificial intelligence in a unified framework built upon situation-theoretic constructs.

Here, S is a sentence—or possibly a smaller or larger unit of meaningful expression for a language—that's written by an author and c is the circumstance in which S is used. R is defined as the language conventions holding between an author and a reader (or better yet, his readership). P, probably the most important part of the equation, is the content of S or, the intended meaning of the author. We assume that the communication between an author and a reader is limited only to written text. Consequently, it is not possible to ask the author about his intention for writing S; that will have to be discovered by a reader.

Papers in this special issue were written upon invitation. They were then subjected to the usual refereeing process of the Journal of Pragmatics. While we have attempted to cover almost all important areas in which context is employed as a conceptual apparatus, our coverage is clearly limited in scope. Accordingly, instead of a general updated overview of the use of context in every conceivable specific field (let's say the state-of-the-art of interdisciplinary research on context: a colossal/impossible enterprise!), we will offer the readers of this special issue an introduction to the problems involved in the study of context by way of eight papers encompassing eight different areas. These are (in alphabetical order): artificial intelligence, bilingualism, child development, cognitive science, conversation analysis, neuroscience, philosophy of language, and pragmatics. Our goal is to propose a multi-faceted view of context, and to stimulate further investigations of this fertile topic, which permeates our lives.

On Crimmins and Perry’s account of propositional attitude ascription (1989), beliefs are concrete cognitive structures—particulars ("things in the head") that belong to an agent and that have a lifetime. They are related to the world and to other cognitive structures and abilities, allowing one to classify the latter by propositional content. Containing ideas and notions as constituents, beliefs are structured entities. The difference between notions and ideas is the difference between an agent’s ways of thinking about individuals vs. properties.

Situated semantics can be regarded as an attempt at placing situational context (context of situation) at the center of all discussions of meaning. Situation theory is a theory of information content that takes context very seriously. Individuals, properties, relations, and spatiotemporal locations are basic constructs of situation theory. Individuals are conceived as invariants; having properties and standing in relations, they tend to persist in time and space. An anchoring function binds the location parameters to appropriate objects present in the grounding situation. Anchoring plays a major role in the working of constraints that include nomic constraints, conventional constraints and conditional constraints. Situation semantics develops a theory of meaning that is based on relations between situations. Situation semantics provides a fundamental framework for realistic semantics. The ideas emerging from research into situation semantics have been combined with linguistic work and have led to numerous useful proposals.

The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing's ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the 'other minds' problem, and similar topics in philosophy of mind are discussed. We also cover the sociological and psychological aspects of the Turing Test. Finally, we look at the current situation and analyze programs that have been developed with the aim of passing the Turing Test. We conclude that the Turing Test has been, and will continue to be, an influential and controversial topic. (This paper was reprinted in: The Turing Test: The Elusive Standard of Artificial Intelligence, J. H. Moor, ed., Kluwer Academic, pp. 23-78, 2003.)

While situation theory and situation semantics provide an appropriate framework for a realistic model-theoretic treatment of natural language, serious thinking on their 'computational' aspects has only recently started. Existing proposals mainly offer a Prolog- or Lisp-like programming environment with varying degrees of divergence from the ontology of situation theory. In this paper, we introduce a computational medium (called BABY-SIT) based on situations. The primary motivation underlying BABY-SIT is to facilitate the development and testing of programs in domains ranging from linguistics to artificial intelligence in a unified framework built upon situation-theoretic constructs.

Strawson proposed in the early seventies an attractive threefold distinction regarding how context bears on the meaning of 'what is said' when a sentence is uttered. The proposed scheme is somewhat crude and, being aware of this aspect, Strawson himself raised various points to make it more adequate. In this paper, we review the scheme of Strawson, note his concerns, and add some of our own. However, our main point is to defend the essence of Strawson's approach and to recommend it as a starting point for research into intended meaning and context.

"Language has never been accessible to me in the way that it was for Sachs. I'm shut off from my own thoughts, trapped in a no-man's-land between feeling and articulation, and no matter how hard I try to express myself, I can rarely come up with more than a confused stammer. Sachs never had any of these difficulties. Words and things matched up for him, whereas for me they are constantly breaking apart, flying off in a hundred different directions. I spend most of my time picking up the pieces and gluing them back together, but Sachs never had to stumble around like that, hunting through garbage dumps and trash bins, wondering if he hadn't fit the wrong pieces next to each other. His uncertainties were of a different order, but no matter how hard life became for him in other ways, words were never his problem." -Paul Auster, Leviathan.