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  • Articles  (16)
  • Artificial intelligence  (16)
  • Springer  (16)
  • American Meteorological Society
  • Elsevier
  • 1995-1999  (9)
  • 1990-1994  (7)
  • 1965-1969
  • 1955-1959
  • 1950-1954
  • 1999  (3)
  • 1995  (6)
  • 1990  (7)
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  • Computer Science  (16)
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  • Articles  (16)
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  • Springer  (16)
  • American Meteorological Society
  • Elsevier
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  • 1995-1999  (9)
  • 1990-1994  (7)
  • 1965-1969
  • 1955-1959
  • 1950-1954
Year
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  • 1
    Electronic Resource
    Electronic Resource
    AI and human society (1999)
    Springer
    AI & society 13 (1999), S. 312-321 
    Details
    ISSN: 1435-5655
    Keywords: Artificial intelligence ; Free time ; Human-centred education ; Human-machine boundary ; Human nature ; Work
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper considers the impact of the AI R&D programme on human society and the individual human being on the assumption that a full realisation of the engineering objective of AI, namely, construction of human-level, domain-independent intelligent entities, is possible. Our assumption is essentially identical tothe maximum progress scenario of the Office of Technology Assessment, US Congress. Specifically, the first section introduces some of the significant issues on the relational nexus among work, education and the human-machine boundary. In particular, based on a Russellian conception of rationality I briefly argue that we need to change our related conceptions of work, employment and free time, through a new human-centred education. On the human-machine boundary problem, I make a couple of tentative suggestions and put forward some crucial open questions. Section two discusses the impact of the emerging machine intelligence on human nature both as modification of its self-image, keeping human nature itself unchanged, and its potential for altering human nature itself. I briefly argue that: (i) in a certain context, the question of the supremacy or uniqueness of human intelligence loses much, if not all, of its ‘weight’; and (ii) appearance of Robot-X species would immortalise the human spirit.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01174784
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  • 2
    Electronic Resource
    Electronic Resource
    Materialism and the “problem” of quantum measurement (1995)
    Springer
    Minds and machines 5 (1995), S. 207-217 
    Details
    ISSN: 1572-8641
    Keywords: Artificial intelligence ; cognitive science ; consciousness ; cosmology ; decoherence ; materialism ; measurement theory ; objectivity ; physics ; pointer basis ; preferred basis ; quantum mechanics ; state vector reduction ; subjectivity ; superselection
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Philosophy
    Notes: Abstract For nearly six decades, the conscious observer has played a central and essential rôle in quantum measurement theory. I outline some difficulties which the traditional account of measurement presents for material theories of mind before introducing a new development which promises to exorcise the ghost of consciousness from physics and relieve the cognitive scientist of the burden of explaining why certain material structures reduce wavefunctions by virtue of being conscious while others do not. The interactive decoherence of complex quantum systems reveals that the oddities and complexities of linear superposition and state vector reduction are irrelevant to computational aspects of the philosophy of mind and that many conclusions in related fields are ill founded.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00974744
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  • 3
    Electronic Resource
    Electronic Resource
    Hownot to demarcate cognitive science and folk psychology: A response to Pickering and Chater (1995)
    Springer
    Minds and machines 5 (1995), S. 339-355 
    Details
    ISSN: 1572-8641
    Keywords: Artificial intelligence ; cognitive science ; folk psychology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Philosophy
    Notes: Abstract Pickering and Chater (P&C) maintain that folk psychology and cognitive science should neither compete nor cooperate. Each is an “independent enterprise,” with a distinct subject matter and characteristic modes of explanation. P&C's case depends upon their characterizations of cognitive science and folk psychology. We question the basis for their characterizations, challenge both the coherence and the individual adequacy of their contrasts between the two, and show that they waver in their views about the scope of each. We conclude that P&C do not so muchdiscover ascreate the gap they find between folk psychology and cognitive science. It is an artifact of their implausible and unmotivated attempt to demarcate the two areas, and of the excessively narrow accounts they give of each.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00974749
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  • 4
    Electronic Resource
    Electronic Resource
    Heuristic evaluation functions in artificial intelligence search algorithms (1995)
    Springer
    Minds and machines 5 (1995), S. 489-498 
    Details
    ISSN: 1572-8641
    Keywords: Artificial intelligence ; heuristics ; search ; two-player games ; constraint-satisfaction
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Philosophy
    Notes: Abstract We consider a special case of heuristics, namely numeric heuristic evaluation functions, and their use in artificial intelligence search algorithms. The problems they are applied to fall into three general classes: single-agent path-finding problems, two-player games, and constraint-satisfaction problems. In a single-agent path-finding problem, such as the Fifteen Puzzle or the travelling salesman problem, a single agent searches for a shortest path from an initial state to a goal state. Two-player games, such as chess and checkers, involve an adversarial relationship between two players, each trying to win the game. In a constraint-satisfaction, problem, such as the 8-Queens problem, the task is to find a state that satisfies a set of constraints. All of these problems are computationally intensive, and heuristic evaluation functions are used to reduce the amount of computation required to solve them. In each case we explain the nature of the evaluation functions used, how they are used in search algorithms, and how they can be automatically learned or acquired.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00974979
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  • 5
    Electronic Resource
    Electronic Resource
    Computationalism (1995)
    Springer
    Minds and machines 5 (1995), S. 517-524 
    Details
    ISSN: 1572-8641
    Keywords: Artificial intelligence ; cognitive science ; Lucas's argument ; incompleteness ; Chinese room ; embodiedness
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Philosophy
    Notes: Abstract Computationalism, the notion that cognition is computation, is a working hypothesis of many AI researchers and Cognitive Scientists. Although it has not been proved, neither has it been disproved. In this paper, I give some refutations to some well-known alleged refutations of computationalism. My arguments have two themes: people are more limited than is often recognized in these debates; computer systems are more complicated than is often recognized in these debates. To underline the latter point, I sketch the design and abilities of a possible embodied computer system.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00974982
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  • 6
    Electronic Resource
    Electronic Resource
    Communications, artificial life, and art (1999)
    Springer
    Artificial life and robotics 3 (1999), S. 190-196 
    Details
    ISSN: 1614-7456
    Keywords: Communication ; Interaction ; Artificial intelligence ; Art
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Studies that examine how the computer can support human communication have been the main research issue for artificial intelligence (AI) researchers. However, since human communication has various aspects, it is necessary for researchers to take into account other approaches. This paper considers the basic issues of human communication, and points out that the artificial life (AL) approach and the artistic approach should be integrated with the conventional AI approach. It also presents examples of research being performed based on this perspective.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02481138
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  • 7
    Electronic Resource
    Electronic Resource
    Cognitive robotics: a new approach to artificial intelligence (1999)
    Springer
    Artificial life and robotics 3 (1999), S. 221-224 
    Details
    ISSN: 1614-7456
    Keywords: Behavior-based robotics ; Artificial intelligence ; Cognition
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper describes a research program about how to achieve artificial intelligence by building robots. It is part of the behavior-oriented AI approach, but differs in some of its hypotheses and methodological approach.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02481184
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  • 8
    Electronic Resource
    Electronic Resource
    A survey of reasoning procedures in knowledge based systems for economics and management (1990)
    Springer
    Computational economics 3 (1990), S. 3-22 
    Details
    ISSN: 1572-9974
    Keywords: Artificial intelligence ; reasoning ; economics ; management ; object oriented design ; conflicts ; knowledge based systems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract This paper surveys reasoning and inference strategies as especially relevant for knowledge based systems in economics and management. This requires elements of object oriented features, numerical and text constraints, search over time, game power conflict resolution. Specific functionalities are discussed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00435401
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  • 9
    Electronic Resource
    Electronic Resource
    Industry structure modeling for competitive analysis: An integrated AI and systems approach (1990)
    Springer
    Computational economics 3 (1990), S. 43-61 
    Details
    ISSN: 1572-9974
    Keywords: Artificial intelligence ; expert system ; competitive analysis ; market share estimation ; industry structure modelling ; polyolefins industry ; mathematical systems modelling
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract This paper describes a ‘new’ approach to model the industry structure that will determine the market share equilibrium in a competitive environment. This approach takes advantage of certain developments in the Expert Systems area in the field of Artificial Intelligence to organize qualitative knowledge of industry structure, and combines such a knowledge base with mathematical systems modeling techniques to develop a market share equilibrium model. The rich structural information embedded in the model makes it potentially a very powerful tool for use in industry assessment and competitive strategy development. One version of the model is implemented in SRI International. The system is fully interactive and is currently used to assess the competitive environment for the polyolefins industry.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00435403
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  • 10
    Electronic Resource
    Electronic Resource
    Generic Expert Systems for Management Applications: The Operations Advisor and the Management Advisor (1990)
    Springer
    Computational economics 3 (1990), S. 167-175 
    Details
    ISSN: 1572-9974
    Keywords: Artificial intelligence ; expert system ; operations management ; finance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract The Operations Advisor and the Management Advisor are AI-based executive decision support systems. The Operations Advisor (OA) enables managers to improve manufacturing strategy. It makes possible manufacturing policies that take full advantage of strategic interactions among capacity utilization, inventories, lead times, and unit costs. The Management Advisor (MA) values strategic business proposals (building a new plant, developing a new product, etc.). It helps managers assess the attractiveness of new business opportunities, and the impact of proposed changes in existing business policy. Artificial intelligence methodologies in the MA and the OA allow us to combine conventional analytic techniques with expert knowledge and experience. They also provide an extremely high level or user facilitation, control, and freedom from error, thus substantially improving overall business productivity. We begin with a description of the design strategy underlying these two generic AI-based management applications. Then we consider how this strategy is realized in the OA and the MA, and the productivity benefits it provides to users.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00436713
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  • 11
    Electronic Resource
    Electronic Resource
    Control metaphors in the modelling of economic learning and decision-making behaviour (1995)
    Springer
    Computational economics 8 (1995), S. 283-301 
    Details
    ISSN: 1572-9974
    Keywords: Artificial intelligence ; Uncertainty ; Genetic Algorithms ; Knowledge-based systems ; Economic complexity
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract Learning is represented in economic models either as a process of estimating equations which are known to be correct representations of the environment or as a process of sampling from a known probability distribution. It is arguably more natural to represent leaning as the specification of equations or other relationships in conditions where information processing capacity is not sufficiently powerful as to enable agents to identify such global characteristics of the whole information set as the moments of a probability distribution. Techniques drawn from the literature on machine learning and on knowledge-based systems are coming into use as tools for modelling learning in such conditions. In this paper I describe the key differences between the older and newer approaches to the modelling of learning and decision-making in terms of two metaphors: the menu and the agenda. Two agenda-type algorithms—a genetic algorithm and a production system — are applied to a simple economic model to show that they imply quite different descriptions of learning and decision-making. Moreover, the production system finds the optimal behaviour orders of magnitude faster than the genetic algorithm because — it is suggested — it is the better descriptor of actual strategic decision-making behaviour in normally complex economic conditions.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01299735
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  • 12
    Electronic Resource
    Electronic Resource
    What can the history of AI learn from the history of science? (1990)
    Springer
    AI & society 4 (1990), S. 232-241 
    Details
    ISSN: 1435-5655
    Keywords: Artificial intelligence ; History of science ; Sociology of knowledge
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract There have been few attempts, so far, to document the history of artificial intelligence. It is argued that the “historical sociology of scientific knowledge” can provide a broad historiographical approach for the history of AI, particularly as it has proved fruitful within the history of science in recent years. The article shows how the sociology of knowledge can inform and enrich four types of project within the history of AI; organizational history; AI viewed as technology; AI viewed as cognitive science and historical biography. In the latter area the historical treatments of Darwin and Turing are compared to warn against the pitfalls of “rational reconstructions” of the past.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01889942
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  • 13
    Electronic Resource
    Electronic Resource
    Active symbols and internal models: Towards a cognitive connectionism (1990)
    Springer
    AI & society 4 (1990), S. 51-71 
    Details
    ISSN: 1435-5655
    Keywords: Artificial intelligence ; Connectionism ; Human cognition ; Symbol systems ; Behaviorism ; Learning ; Knowledge structures
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In the first section of the article, we examine some recent criticisms of the connectionist enterprise: first, that connectionist models are fundamentally behaviorist in nature (and, therefore, non-cognitive), and second that connectionist models are fundamentally associationist in nature (and, therefore, cognitively weak). We argue that, for a limited class of connectionist models (feed-forward, pattern-associator models), the first criticism is unavoidable. With respect to the second criticism, we propose that connectionist modelsare fundamentally associationist but that this is appropriate for building models of human cognition. However, we do accept the point that there are cognitive capacities for which any purely associative model cannot provide a satisfactory account. The implication that we draw from is this is not that associationist models and mechanisms should be scrapped, but rather that they should be enhanced. In the next section of the article, we identify a set of connectionist approaches which are characterized by “active symbols” — recurrent circuits which are the basis of knowledge representation. We claim that such approaches avoid criticisms of behaviorism and are, in principle, capable of supporting full cognition. In the final section of the article, we speculate at some length about what we believe would be the characteristics of a fully realized active symbol system. This includes both potential problems and possible solutions (for example, mechanisms needed to control activity in a complex recurrent network) as well as the promise of such systems (in particular, the emergence of knowledge structures which would constitute genuine internal models).
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01889764
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  • 14
    Electronic Resource
    Electronic Resource
    Connectionism and artificial intelligence as cognitive models (1990)
    Springer
    AI & society 4 (1990), S. 115-136 
    Details
    ISSN: 1435-5655
    Keywords: Neural networks ; Artificial intelligence ; Representations ; Cognitive modelling ; Epistemology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The current renewal of connectionist techniques using networks of neuron-like units has started to have an influence on cognitive modelling. However, compared with classical artificial intelligence methods, the position of connectionism is still not clear. In this article artificial intelligence and connectionism are systematically compared as cognitive models so as to bring out the advantages and shortcomings of each. The problem of structured representations appears to be particularly important, suggesting likely research directions.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01889639
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  • 15
    Electronic Resource
    Electronic Resource
    The role of “craft language” in learning “Waza” (1990)
    Springer
    AI & society 4 (1990), S. 137-146 
    Details
    ISSN: 1435-5655
    Keywords: Waza ; Skill ; Craft language ; Kata ; Katachi ; Habitus ; Human intelligence ; Artificial intelligence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The role of “craft language” in the process of teaching (learning) “Waza” (skill) will be discussed from the perspective of human intelligence. It may be said that the ultimate goal of learning “Waza” in any Japanese traditional performance is not the perfect reproduction of the teaching (learning) process of “Waza”. In fact, a special metaphorical language (“craft language”) is used, which has the effect of encouraging the learner to activate his creative imagination. It is through this activity that the he learns his own “habitus” (“Kata”). It is suggested that, in considering the difference of function between natural human intelligence and artificial intelligence, attention should be paid to the imaginative activity of the learner as being an essential factor for mastering “Kata”.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01889640
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  • 16
    Electronic Resource
    Electronic Resource
    Cognition and decision in biomedical artificial intelligence: From symbolic representation to emergence (1995)
    Springer
    AI & society 9 (1995), S. 138-160 
    Details
    ISSN: 1435-5655
    Keywords: Artificial intelligence ; Medical-informatics ; Medical information systems ; Medical decision making ; Machine-learning ; Cognitive science ; Expert systems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper presents work in progress on artificial intelligence in medicine (AIM) within the larger context of cognitive science. It introduces and develops the notion ofemergence both as an inevitable evolution of artificial intelligence towards machine learning programs and as the result of a synergistic co-operation between the physician and the computer. From this perspective, the emergence of knowledge takes placein fine in the expert's mind and is enhanced both by computerised strategies of induction and deduction, and by software abilities to dialogue, co-operate and function as a cognitive extension of the physician's intellectual capabilities. The proposed methodology gives the expert a prominent role which consists, first, of faithfully enunciating the descriptive features of his medical knowledge, thus giving the computer a precise description of his own perception of basic medicine, and secondly, of painstakingly gathering patients into computerised case bases which simulate exhaustive long-term memory. The AI capacities for knowledge elaboration are then triggered, giving rise to mathematically optimal diagnoses, prognoses, or treatment protocols which the physician may then evaluate, accept, reject, or adapt at his convenience, and finally append to a knowledge base. The idea of emergence embraces many issues concerning the purpose and intent of artificial intelligence in medical practice. Particularly, we address the representation problem as it is raised by classical decisional knowledge-based systems, and develop the notions of classifiers and hybrid systems as possible answers to this problem. Finally, since the whole methodology touches the problem of technological investment in health care, now inherent in modern medical practice, some ethical considerations accompany the exposé.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01210601
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