Artificial intelligence has often been seen as an attempt to reduce the natural mind to informational processes and, consequently, to naturalize philosophy. The many criticisms that were addressed to the so-called “old-fashioned AI” do not concern this attempt itself, but the methods it used, especially the reduction of the mind to a symbolic level of abstraction, which has often appeared to be inadequate to capture the richness of our mental activity. As a consequence, there were many efforts to evacuate the (...) semantical models in favor of elementary physiological mechanisms simulated by information processes. However, these views, and the subsequent criticisms against artificial intelligence that they contain, miss the very nature of artificial intelligence, which is not reducible to a “science of the nature”, but which directly impacts our culture. More precisely, they lead to evacuate the role of the semantic information. In other words, they tend to throw the baby out with the bath-water. This paper tries to revisit the epistemology of artificial intelligence in the light of the opposition between the “sciences of nature” and the “sciences of culture”, which has been introduced by German neo-Kantian philosophers. It then shows how this epistemological view opens on the many contemporary applications of artificial intelligence that have already transformed—and will continue to transform—all our cultural activities and our world. Lastly, it places those perspectives in the context of the philosophy of information and more particularly it emphasizes the role played by the notions of context and level of abstraction in artificial intelligence. (shrink)

Situational irony concerns what it is about a situation that causes people to describe it as ironic. Although situational irony is as complex and commonplace as verbal and literary irony, it has received nowhere near the same attention from cognitive scientists and other scholars. This paper presents the bicoherence theory of situational irony, based on the theory of conceptual coherence (Kunda & Thagard, 1996; Thagard & Verbeurgt, 1998). On this theory, a situation counts as ironic when it is conceived as (...) having a bicoherent conceptual structure, adequate cognitive salience, and evokes an appropriate configuration of emotions. The theory is applied to a corpus of 250 examples of situational ironies gathered automatically from electronic news sources. A useful taxonomy of situational ironies is produced, new predictions and insights into situational irony are discussed, and extensions of the theory to other forms of irony are examined. (shrink)

Human agents draw a variety of inferences effortlessly, spontaneously, and with remarkable efficiency – as though these inferences were a reflexive response of their cognitive apparatus. Furthermore, these inferences are drawn with reference to a large body of background knowledge. This remarkable human ability seems paradoxical given the complexity of reasoning reported by researchers in artificial intelligence. It also poses a challenge for cognitive science and computational neuroscience: How can a system of simple and slow neuronlike elements represent a large (...) body of systemic knowledge and perform a range of inferences with such speed? We describe a computational model that takes a step toward addressing the cognitive science challenge and resolving the artificial intelligence paradox. We show how a connectionist network can encode millions of facts and rules involving n-ary predicates and variables and perform a class of inferences in a few hundred milliseconds. Efficient reasoning requires the rapid representation and propagation of dynamic bindings. Our model (which we refer to as SHRUTI) achieves this by representing (1) dynamic bindings as the synchronous firing of appropriate nodes, (2) rules as interconnection patterns that direct the propagation of rhythmic activity, and (3) long-term facts as temporal pattern-matching subnetworks. The model is consistent with recent neurophysiological evidence that synchronous activity occurs in the brain and may play a representational role in neural information processing. The model also makes specific psychologically significant predictions about the nature of reflexive reasoning. It identifies constraints on the form of rules that may participate in such reasoning and relates the capacity of the working memory underlying reflexive reasoning to biological parameters such as the lowest frequency at which nodes can sustain synchronous oscillations and the coarseness of synchronization. (shrink)

Although the connectionist approach has lead to elegant solutions to a number of problems in cognitive science and artificial intelligence, its suitability for dealing with problems in knowledge representation and inference has often been questioned. This paper partly answers this criticism by demonstrating that effective solutions to certain problems in knowledge representation and limited inference can be found by adopting a connectionist approach. The paper presents a connectionist realization of semantic networks, that is, it describes how knowledge about concepts, their (...) properties, and the hierarchical relationship between them may be encoded as an interpreter‐free massively parallel network of simple processing elements that can solve an interesting class of inheritance and recognition problems extremely fast—in time proportional to the depth of the conceptual hierarchy. The connectionist realization is based on an evidential formulation that leads to principled solutions to the problems of exceptions and conflicting multiple inheritance situations during inheritance, and the best‐match or partial‐match computation during recognition. The paper also identifies constraints that must be satisfied by the conceptual structure in order to arrive at an efficient parallel realization. (shrink)

The resolution of ambiguities is one of the central problems for Machine Translation. In this paper we propose a knowledge-based approach to disambiguation which uses Description Logics (dl) as representation formalism. We present the process of anaphora resolution implemented in the Machine Translation systemfast and show how thedl systemback is used to support disambiguation.The disambiguation strategy uses factors representing syntactic, semantic, and conceptual constraints with different weights to choose the most adequate antecedent candidate. We show how these factors can be (...) declaratively represented as defaults inback. Disambiguation is then achieved by determining the interpretation that yields a qualitatively minimal number of exceptions to the defaults, and can thus be formalized as exception minimization. (shrink)

Establishing reasonable, prior distributions remains a significant obstacle for the construction of probabilistic expert systems. Human assessment of chance is often relied upon for this purpose, but this has the drawback of being inconsistent with axioms of probability. This article advances a method for extracting a coherent distribution of probability from human judgment. The method is based on a psychological model of probabilistic reasoning, followed by a correction phase using linear programming.

Starting with the facts that not everything that is understood is remembered, and that not everything that is remembered is understood. this paper urges that models of language processing should be able to make a distinction between comprehension and memory. To this end. a case is made for a spreading activation process as being the essential ingredient of the comprehension process. It is argued that concepts activated during comprehension not only restrict the search set for candidate concepts to be used (...) in a top‐down fashion, they also constitute part of an episodic representation that can come to be p e of long‐term memory. The way in which these representations atrophy is discussed, as is the way in which their idiosyncratic components are eliminated in producing representations in semantic memory. Some observations on the comprehension and memory of text are made and arguments are presented to show how intrusions and omissions in recall can be handled. Some existing experimental data is reanalyzed in terms of the proposed model and alternative interpretations consistent with the model are shown to be possible. (shrink)

An integrated statement is made concerning the semantic status of nodes in a propositional semantic network, claiming that such nodes represent only intensions. Within the network, the only reference to extensionality is via a mechanism to assert that two intensions have the same extension in same world. This framework is employed in three application problems to illustrate the nature of its solutions.The formalism used here utilizes only assertional information and no structural, or definitional, information. This restriction corresponds to many of (...) the psychologically motivated network models. Some of the psychological implications of network processes called node merging and node splitting are discussed. Additionally, it is pointed out that both our networks and the psychologically based networks are prone to memory confusions about knowing unless augmented by domain‐specific inference processes, or by structural information. (shrink)

In this paper a logical interpretation of semantic nets and graph grammars is proposed for modelling natural language understanding and creating language understanding computer systems. An example of parsing a Finnish question by graph grammars and inferring the answer to it by a semantic net representation is provided.

This study presents original evidence that abstract and concrete concepts are organized and represented differently in the mind, based on analyses of thousands of concepts in publicly available data sets and computational resources. First, we show that abstract and concrete concepts have differing patterns of association with other concepts. Second, we test recent hypotheses that abstract concepts are organized according to association, whereas concrete concepts are organized according to (semantic) similarity. Third, we present evidence suggesting that concrete representations are more (...) strongly feature-based than abstract concepts. We argue that degree of feature-based structure may fundamentally determine concreteness, and we discuss implications for cognitive and computational models of meaning. (shrink)

The paper examines locative expressions and shows that an adequate account of their meaning must be based on two essential understandings: First, the simple spatial relation, often given as the meaning of the spatial prepositions, is only an “ideal” from which there are deviations in context; second, a level of “geometric conceptualization” mediates between “the world as it is” and language. Pragmatic “near principles” are formulated to explain some deviations from the ideal and several other apparent irregularities of prepositional use. (...) A set of “use types” of the ideal meaning is proposed to account for conventional aspects of locative meaning. The paper concludes with a discussion of the consequences of this description of locative expressions for artificial intelligence and linguistics. (shrink)

This paper studies the relationship of Artificial Intelligence to the study of language and the representation of the underlying knowledge which supports the comprehension process. It develops the view that intelligence is based on the ability to use large amounts of diverse kinds of knowledge in procedural ways, rather than on the possession of a few general and uniform principles. The paper also provides a unifying thread to a variety of recent approaches to natural language comprehension. We conclude with a (...) brief discussion of how Artificial Intelligence may have a radical impact on education if the principles which it utilizes to explore the representation and use of knowledge are made available to the student to use in his own learning experiences. (shrink)

‘External memories’ raise a question about context: ‘external to what?’ External memory is a technical term applied to everything that can be memorized in an individual's environment. As a general rule I have decided to retain the technical terms that characterize the area of the topic under discussion. It was Ted Nelson who coined the word hypertext in 1967 to signify non-sequential writing as well as a computer technology that allowed the user to move about freely by means of software (...) links. I shall use the term software to mean computer programs. Electronic publishing started with the Xanadu system developed by Nelson. At the lowest level a hypertext is a system for managing databases that allows the user to connect together information screens using links. It is a collection of texts interconnected by means of interactive switches. This dynamic presentation of non-linear texts could not be printed on a conventional page. Hypertext allows the origin of a piece of information to be traced. In this article traceability is synonymous with explanation: ‘Why was this equipment designed in one way rather than another?’ It is about discovering the route of the design process that led to the eventual idea for the equipment. The necessary explanations are often required long after decisions were made, and this is why traceability is a matter of memory. The term agent is often used to mean those members of a community that act on its behalf. There are agents for a company or public department. There are biological agents. In a non-technological world traceability is ideally carried out by human agents who explain to other human agents. The term agent has been extended into the computer world to mean software to which the user delegates, sometimes unwittingly, tasks of varying complexity. These are then called software agents. In this article I refer to agent in its wider meaning, to be understood as an actor or an entity able to act in a limited context and having a quite specific role and appropriate resources. (shrink)

Some thoughts just come to mind together. This is usually thought to happen because they are connected by associations, which the mind follows. Such an explanation assumes that there is a particular kind of simple psychological process responsible. This view has encountered criticism recently. In response, this paper aims to characterize a general understanding of associative simplicity, which might support the distinction between associative processing and alternatives. I argue that there are two kinds of simplicity that are treated as characteristic (...) of association, and as a result three possible versions of associative processing. This provides a framework that informs our understanding of association as a current and historical concept, including how various specific versions in different parts of psychology relate to one another. This framework can also guide debates over normative evaluations of actions produced by processes thought to be associative. (shrink)

Some thoughts just come to mind together. This is usually thought to happen because they are connected by associations, which the mind follows. Such an explanation assumes that there is a particular kind of simple psychological process responsible. This view has encountered criticism recently. In response, this paper aims to characterize a general understanding of associative simplicity, which might support the distinction between associative processing and alternatives. I argue that there are two kinds of simplicity that are treated as characteristic (...) of association, and as a result three possible versions of associative processing. This provides a framework that informs our understanding of association as a current and historical concept, including how various specific versions in different parts of psychology relate to one another. This framework can also guide debates over normative evaluations of actions produced by processes thought to be associative. (shrink)