Artificial intelligence : its scope and limits
著者
書誌事項
Artificial intelligence : its scope and limits
(Studies in cognitive systems, v. 4)
Kluwer , Sold and distributed in the U.S.A. and Canada by Kluwer, c1990
- : hbk
- : pbk
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注記
Includes bibliographical references (p. 305-315) and indexes
内容説明・目次
内容説明
This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psycholo gy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial in telligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these prob lems and domains, empirical, experimental, and methodological studies will also appear from time to time. The perspective that prevails in artificial intelligence today suggests that the theory of computability defines the boundaries of the nature of thought, precisely because all thinking is computational. This paradigm draws its inspiration from the symbol-system hypothesis of Newell and Simon and finds its culmination in the computational conception of lan guage and mentality. The "standard conception" represented by these views is subjected to a thorough and sustained critique in the pages of this book. Employing a distinction between systems for which signs are signif icant for the users of a system and others for which signs are significant for use by a system, I have sought to define the boundaries of what AI, in principle, may be expected to achieve.
目次
I: Metamentality.- 1. What is Artificial Intelligence?.- Criteria of Intelligence.- The Turing Test.- The Chinese Room.- The Korean Room.- Varieties of Intelligence.- Rationality.- Intentionality.- Humanity.- The Aim of this Inquiry.- Behaviorism.- Extensionality.- Reductionism.- 2. Symbol Systems and Semiotic Systems.- Peirce's Theory of Signs.- Abstract and Physical Systems.- Causal and Semiotic Systems.- The Varieties of Semiotic Systems.- Symbol and Causal Systems.- Symbol and Semiotic Systems.- The Symbol and Semiotic-System Hypotheses.- What about Humans and Machines?.- What Difference Does It Make?.- 3. Theories of Language and Mentality.- The Computational Conception.- The Parsing Criterion.- Ambiguity and Synonymy.- The Representational Conception.- The Language of Thought.- The Substitutional Criterion.- The Dispositional Conception.- A Theory of Cognition.- The Functional Role Criterion.- Fundamentally Different Systems.- II: Knowledge and Expertise.- 4. The Nature of Knowledge.- Conditions of Knowledge.- The Classic Definition.- Certainty vs. Fallibility.- A Refined Conception.- Language Frameworks.- Analytic Sentences.- A Priori Knowledge.- Modes of Modality.- The Condition of Truth.- Truth and Meaning.- Austin's Conventions.- Appropriate Beliefs.- 5. Varieties of Knowledge.- Ordinary Knowledge.- Common Sense.- Defeasible Reasoning.- Scientific Knowledge.- Laws of Nature.- Lawlike Sentences.- Maximal Specificity.- Epistemic Scorekeeping.- The Frame Problem.- 6. Expert Systems.- The General Conception.- The Choice of an Expert.- The Nature of Expertise.- Scientific Expertise.- Expert Production Systems.- Logical Structure.- Epistemic Contents.- Truth vs. Practicality.- Varieties of Expert Systems.- The Expert System.- The Knowledge-Processing System.- The Expert-Aided Knowledge-Processing System.- III: Representation and Verification.- 7. Knowledge Representation.- Semantic Networks.- Logical Structure.- Epistemic Contents.- Scripts and Frames.- Scripts as Sequences of Frames.- Scripts as Modes of Understanding.- Selecting a Representation Scheme.- Logical Structures.- Epistemic Contents.- Has the Role of Logic Been Misconceived?.- 8. Program Verification.- The Comparison with Mathematics.- Concepts of Verification.- Probable Verifications.- Two Kinds of Complexity.- Theorems, Algorithms, and Programs.- The Deeper Disanalogy.- Programs as Causal Models.- Abstract and Target Machines.- The Ambiguity of "Program Verification".- Programs as Applied Mathematics.- Testing Computer Programs.- Complexity and Reliability.- 9. Minds, Bodies, and Machines.- The Nature of Mind.- Human Cognition.- Machine Mentality.- Minds and Bodies.- Laws of Human Beings.- Laws of Digital Machines.- Other Minds.- Computers and Cognition.- The Cognitive Computer.- Why People Think Computers Can't.- References.- Numbered Definitions.- List of Figures.- Index of Names.- Index of Subjects.
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