Varol Akman

The work described in this report is motivated by the desire to test the expressive possibilities of action language C+. The Causal Calculator (CCalc) is a system that answers queries about action domains described in a fragment of that language. The Zoo World and the Traffic World have been proposed by Erik Sandewall in his Logic Modelling Workshop—an environment for communicating axiomatizations of action domains of nontrivial size. The Zoo World consists of several cages and the exterior, gates between them, and animals of several species, including humans. Actions in this domain include moving within and between cages, opening and closing gates, and mounting and riding animals. The Traffic World includes vehicles moving continuously between road crossings subject to a number of restrictions, such as speed limits and keeping a fixed safety distance away from other vehicles on the road. We show how to represent the two domains in the input language of CCalc, and how to use CCalc to test these representations.

Serious thinking about the computational aspects of situation theory is just starting. There have been some recent proposals in this direction (viz. PROSIT and ASTL), with varying degrees of divergence from the ontology of the theory. We believe that a programming environment incorporating bona fide situation-theoretic constructs is needed and describe our very recent BABY-SIT implementation. A detailed critical account of PROSIT and ASTL is also offered in order to compare our system with these pioneering and influential frameworks.

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.

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.

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.

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.

[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.

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.)

Commonsense reasoning about the physical world, as exemplified by "Iron sinks in water" or "If a ball is dropped it gains speed," will be indispensable in future programs. We argue that to make such predictions (namely, envisioning), programs should use abstract entities (such as the gravitational field), principles (such as the principle of superposition), and laws (such as the conservation of energy) of physics for representation and reasoning. These arguments are in accord with a recent study in physics instruction where expert problem solving is related to the construction of physical representations that contain fictitious, imagined entities such as forces and momenta (Larkin 1983). We give several examples showing the power of physical representations.

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.

Deflationism, one of the influential philosophical doctrines of truth, holds that there is no property of truth, and that overt uses of the predicate "true" are redundant. However, the hypothetical examples used by theorists to exemplify deflationism are isolated sentences, offering little to examine what the predicate adds to meaning within context. We oppose the theory not on philosophical but on empirical grounds. We collect 7,610 occurrences of "it is true that" from 10 influential periodicals published in the United States. We classify and annotate these with respect to the positions of coordinating and subordinating conjunctions that they contain. This way we investigate the contextual relationships between the proposition following "it is true that" with its surroundings. Overall, 34 different syntactical patterns are encountered. In some occurrences of "true", the predicate acts in the same manner as a performative verb does. These occurrences, having been observed in linguistically reliable media, constitute pragmatic counter-examples to deflationism.

The papers that make up this special issue do not take idealized abstractions of context as their point of departure but rather start with the actual phenomena under study and later generalize. We agree that, more often than not, giving a formal model and providing a theory of a loaded notion – such as context – can lead to important insights. Thus, precise models of context and accompanying theories are useful. However, given the widely different fields, methodologies and worldviews within which people study, an approach that starts with the root phenomena/problems and only attempts normalization and generalization post hoc might be a more productive way to proceed.

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.