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Building a person has been an elusive goal in artificial intelligence. This failure, John Pollock argues, is because the problems involved are essentially philosophical; what is needed for the construction of a person is a physical system that mimics human rationality. Pollock describes an exciting theory of rationality and its partial implementation in OSCAR, a computer system whose descendants will literally be persons.In developing the philosophical superstructure for this bold undertaking, Pollock defends the conception of man as an intelligent machine and argues that mental states are physical states and persons are physical objects as described in the fable of Oscar, the self conscious machine.Pollock brings a unique blend of philosophy and artificial intelligence to bear on the vexing problem of how to construct a physical system that thinks, is self conscious, has desires, fears, intentions, and a full range of mental states. He brings together an impressive array of technical work in philosophy to drive theory construction in AI. The result is described in his final chapter on "cognitive carpentry." John Pollock is Professor of Philosophy and Cognitive Science at the University of Arizona. A Bradford Book.
(source: Nielsen Book Data)

This book aims to construct a theory of rational decision making for real, resource-bounded, agents. Such decision making must be based on objective probabilities, rather than subjective probabilities, and cannot be done by choosing single actions with maximal expected values. Actions must be chosen as parts of plans, and plans must be evaluated in the context of other plans.
(source: Nielsen Book Data)

• The problems of knowledge
• foundations theories
• coherence theories
• externalism
• epistemic norms
• epistemology and rationality
• direct realism.
• (source: Nielsen Book Data)

This new edition of the classic "Contemporary Theories of Knowledge" has been updated to include analyses of the recent literature in epistemology. In addition, a new case is made for the strong connection between epistemology and artificial intelligence, as the authors argue that a necessary condition for the correctness of any epistemological theory is that it be possible to build an implemented artificial intelligence system on the basis of it. Like the first edition, the book is a teaching tool, introducing the reader to the fundamental issues and approaches in the filed of epistemology.
(source: Nielsen Book Data)
This new edition of the classic Contemporary Theories of Knowledge has been significantly updated to include analyses of the recent literature in epistemology. Rather than merely making slight amendments to the first edition, Pollock and Cruz have undertaken a groundbreaking assessment of twentieth-century epistemology. This book is both an advanced textbook offering traditional discussions of foundationalism, coherentism, and reliabilism and a detailed treatise on the authors' own distinctive view, direct realism. Written in a clear accessible style, this book will be of interest to students of epistemology and to philosophers in general. Visit our website for sample chapters!.
(source: Nielsen Book Data)

• Rational agents
• epistemology from the design stance
• the structure of defeasible reasoning
• an architecture for epistemic cognition
• plan-based practical reasoning
• the logical structure of plans
• an architecture for planning
• acting
• OSCAR.
• (source: Nielsen Book Data)

A sequel to the author's "How to Build a Person", this work builds upon that theoretical groundwork for the implementation of rationality through artificial intelligence. It argues that progress in AI has stalled because of its creators' reliance upon unformulated intuitions about rationality. Instead, the author bases the OSCAR architecture upon an explicit philosophical theory of rationality, encompassing principles of practical cognition, epistemic cognition and defeasible reasoning. One of the results is the first automated defeasible reasoner capable of reasoning in a rich, logical environment. Underlying the book's thesis is a conviction that the tenets of artificial intelligence and those of philosophy can be complementary and mutually beneficial to each. And, while members of both camps have in recent years grown sceptical of the very possibility of "symbol processing" AI, this book establishes that such an approach to AI can be successful.
(source: Nielsen Book Data)

• 1. Rational agents
• 2. Epistemology from the design stance
• 3. The structure of defeasible reasoning
• 4. An architecture for epistemic cognition
• 5. Plan-based practical reasoning
• 6. The logical structure of plans
• 7. An architecture for planning
• 8. Acting
• 9. OSCAR.

In his groundbreaking new book, John Pollock establishes an outpost at the crossroads where artificial intelligence meets philosophy. Specifically, he proposes a general theory of rationality and then describes its implementation in OSCAR, an architecture for an autonomous rational agent he claims is the "first AI system capable of performing reasoning that philosophers would regard as epistemically sophisticated.".
(source: Nielsen Book Data)
A sequel to Pollock's How to Build a Person, this volume builds upon that theoretical groundwork for the implementation of rationality through artificial intelligence. Pollock argues that progress in AI has stalled because of its creators' reliance upon unformulated intuitions about rationality. Instead, he bases the OSCAR architecture upon an explicit philosophical theory of rationality, encompassing principles of practical cognition, epistemic cognition, and defeasible reasoning. In his groundbreaking new book, John Pollock establishes an outpost at the crossroads where artificial intelligence meets philosophy. Specifically, he proposes a general theory of rationality and then describes its implementation in OSCAR, an architecture for an autonomous rational agent he claims is the first AI system capable of performing reasoning that philosophers would regard as epistemically sophisticated. A sequel to Pollock's How to Build a Person, this volume builds upon that theoretical groundwork for the implementation of rationality through artificial intelligence. Pollock argues that progress in AI has stalled because of its creators' reliance upon unformulated intuitions about rationality. Instead, he bases the OSCAR architecture upon an explicit philosophical theory of rationality, encompassing principles of practical cognition, epistemic cognition, and defeasible reasoning. One of the results is the world's first automated defeasible reasoner capable of reasoning in a rich, logical environment. Underlying Pollock's thesis is a conviction that the tenets of artifical intelligence and those of philosophy can be complementary and mutually beneficial. And, while members of both camps have in recent years grown skeptical of the very possibility of "symbol processing" AI, Cognitive Carpentry establishes that such an approach to AI can be successful. A Bradford Book.
(source: Nielsen Book Data)
A sequel to the author's "How to Build a Person", this work builds upon that theoretical groundwork for the implementation of rationality through artificial intelligence. It argues that progress in AI has stalled because of its creators' reliance upon unformulated intuitions about rationality. Instead, the author bases the OSCAR architecture upon an explicit philosophical theory of rationality, encompassing principles of practical cognition, epistemic cognition and defeasible reasoning. One of the results is the first automated defeasible reasoner capable of reasoning in a rich, logical environment. Underlying the book's thesis is a conviction that the tenets of artificial intelligence and those of philosophy can be complementary and mutually beneficial to each. And, while members of both camps have in recent years grown sceptical of the very possibility of "symbol processing" AI, this book establishes that such an approach to AI can be successful.
(source: Nielsen Book Data)

• 1. Physical Probability;
• 2. Computational Principles;
• 3. Acceptance Rules;
• 4. Direct Inference and Definite Probabilities;
• 5. Induction;
• 6. Recapitulation;
• 7. Exotic Computational Principles;
• 8. Advanced Topics: Defeasible Reasoning;
• 9. Advanced Topics: Acceptance Rules;
• 10. Advanced Topics: Direct Inference;
• 11. Advanced Topics: Induction; Bibliography; Index; A; B; C; D; E; F; G; H; I; J; K; L; M; N; O; P; Q; R; S; T; U; V; W; Appendix: Main Principles.

This book deals with the subject of probabilistic reasoning. Professor Pollock attempts to make general philosophical sense of objective probabilities and he explores their relationship to the problem of induction. He argues that probability is fundamental not only to physical science, but to induction, epistemology, the philosophy of science and to much reasoning of interest to artificial intelligence. He attempts to show how his understanding of probability throws light on these related issues. Pollock's main claim is that the fundamental notion of probability is nomic - that is, it involves the notion of natural law, valid across possible worlds. The various epistemic and statistical conceptions of probability, he demonstrates, are derived from this nomic notion. He goes on to provide a theory of statistical induction; an account of computational principles allowing some probabilities to be derived from others; an account of acceptance rules; and a theory of direct inference.
(source: Nielsen Book Data)

This book deals with the subject of probabilistic reasoning. Professor Pollock attempts to make general philosophical sense of objective probabilities and he explores their relationship to the problem of induction. He argues that probability is fundamental not only to physical science, but to induction, epistemology, the philosophy of science and to much reasoning of interest to artificial intelligence. He attempts to show how his understanding of probability throws light on these related issues. Pollock's main claim is that the fundamental notion of probability is nomic - that is, it involves the notion of natural law, valid across possible worlds. The various epistemic and statistical conceptions of probability, he demonstrates, are derived from this nomic notion. He goes on to provide a theory of statistical induction; an account of computational principles allowing some probabilities to be derived from others; an account of acceptance rules; and a theory of direct inference.
(source: Nielsen Book Data)

This book deals with the subject of probabilistic reasoning. Professor Pollock attempts to make general philosophical sense of objective probabilities and he explores their relationship to the problem of induction. He argues that probability is fundamental not only to physical science, but to induction, epistemology, the philosophy of science and to much reasoning of interest to artificial intelligence. He attempts to show how his understanding of probability throws light on these related issues. Pollock's main claim is that the fundamental notion of probability is nomic - that is, it involves the notion of natural law, valid across possible worlds. The various epistemic and statistical conceptions of probability, he demonstrates, are derived from this nomic notion. He goes on to provide a theory of statistical induction; an account of computational principles allowing some probabilities to be derived from others; an account of acceptance rules; and a theory of direct inference.
(source: Nielsen Book Data)

• Part 1 Set theory: the logical framework
• the basic concepts of set theory
• relations
• functions
• recursive definitions
• arithmetic. Part 2 Logic: the predicate calculus
• first-order theories
• higher order logic.
• (source: Nielsen Book Data)

This book introduces the technical tools and concepts that are indispensable for advanced work in philosophy. Beginning with the fundamentals of set theory, the author guides the reader through relations, functions and the theory of arithmetic before using these tools to clarify the metatheory of the predicate calculus. There are discussions of recursive definitions, Godel's Theorem, and completeness for the predicate calculus. The text emphasizes the structure of these systems and the metatheory behind them.
(source: Nielsen Book Data)

Building a person has been an elusive goal in artificial intelligence. This failure, John Pollock argues, is because the problems involved are essentially philosophical; what is needed for the construction of a person is a physical system that mimics human rationality. Pollock describes an exciting theory of rationality and its partial implementation in OSCAR, a computer system whose descendants will literally be persons.In developing the philosophical superstructure for this bold undertaking, Pollock defends the conception of man as an intelligent machine and argues that mental states are physical states and persons are physical objects as described in the fable of Oscar, the self conscious machine.Pollock brings a unique blend of philosophy and artificial intelligence to bear on the vexing problem of how to construct a physical system that thinks, is self conscious, has desires, fears, intentions, and a full range of mental states. He brings together an impressive array of technical work in philosophy to drive theory construction in AI. The result is described in his final chapter on "cognitive carpentry.""A Bradford Book".
(source: Nielsen Book Data)

Building a person has been an elusive goal in artificial intelligence. This failure, John Pollock argues, is because the problems involved are essentially philosophical; what is needed for the construction of a person is a physical system that mimics human rationality. Pollock describes an exciting theory of rationality and its partial implementation in OSCAR, a computer system whose descendants will literally be persons.In developing the philosophical superstructure for this bold undertaking, Pollock defends the conception of man as an intelligent machine and argues that mental states are physical states and persons are physical objects as described in the fable of Oscar, the self conscious machine.Pollock brings a unique blend of philosophy and artificial intelligence to bear on the vexing problem of how to construct a physical system that thinks, is self conscious, has desires, fears, intentions, and a full range of mental states. He brings together an impressive array of technical work in philosophy to drive theory construction in AI. The result is described in his final chapter on "cognitive carpentry." John Pollock is Professor of Philosophy and Cognitive Science at the University of Arizona. A Bradford Book.
(source: Nielsen Book Data)

• Part 1 The problems of knowledge: skeptical problems
• knowledge and justification
• areas of knowledge
• theories of knowledge. Part 2 Foundations theories: motivation
• basic beliefs
• epistemic ascent
• reasoning and memory
• reconsideration of epistemologically basic beliefs. Part 3 Coheremce theories: motivation a taxonomy of coherence theories
• nondoxastic theories and direct realism. Part 4 Externalism: motivation
• varities of probability
• probabilism
• reliabilism. Part 5 Epistemic norms: recapitulation
• epistemic norms
• how do epistemic norms regulate?
• the refutation of externalism
• man as a cognitive machine
• a naturalistic internalism
• direct realism. Appendix: The Getting problem - objective epistemic justification, social aspects of knowledge.
• (source: Nielsen Book Data)

Designed as a text for advanced philosophy students, this book introduces the reader to the fundamental issues and approaches in the field of epistemology. The author provides a critical survey and assessment of all major competing theories of knowledge - foundations theories, coherence theories, direct realism, reliabilism and probabilism. Pollock clarifies the dinstinguishing features of each theory and analyzes the arguments supporting or refuting them. He makes a strong case for a particular theory - the nondoxastic internalist theory of direct realism - as the most logically defensible.
(source: Nielsen Book Data)

• Frontmatter
• Contents
• Preface
• I. The Statemental Theory of Meaning
• II. Traditional Theories of Proper Names
• III. The Meaning of a Proper Name
• IV. Singular Terms
• V. The Traditional Theory of Predicates
• VI. Synthetic Predicates
• VII. Nonsynthetic Predicates
• VIII. The Alethic Modalities
• IX. Doxastic and Epistemic Sentences
• X. Languages, Institutions, and Conventions
• XI. Stating
• XII. Nondeclarative Sentences
• Appendix: A General Statemental Semantics
• Bibliography
• Index.

Most philosophical theories of language have assumed that statements (products of assertion) and propositions (objects of belief) are the same things. John L. Pollock denies this, maintaining that even when the speaker is perfectly sincere, what he is thinking need not be the same thing as what he is saying. Originally published in 1982. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
(source: Nielsen Book Data)

• *Frontmatter, pg. i*Preface, pg. vii*Contents, pg. ix*Chapter One. What Is an Epistemological Problem?, pg. 1*Chapter Two. The Structure of Epistemic Justification, pg. 23*Chapter Three. Theories of Perceptual Knowledge, pg. 50*Chapter Four. Incorrigibility, pg. 71*Chapter Five. Perceptual Attributes, pg. 80*Chapter Six. The Reidentification of Physical Things, pg. 134*Chapter Seven. Memory and Historical Knowledge, pg. 175*Chapter Eight. Induction, pg. 204*Chapter Nine. The Concept of a Person, pg. 249*Chapter Ten. Truths of Reason, pg. 300*References, pg. 341*Index, pg. 347.
• (source: Nielsen Book Data)

One of the most firmly entrenched beliefs of contemporary philosophy is that the only way to analyze a concept is to state its truth conditions. In epistemology this has led to the search for reductive analyses, to phenomenalism, behaviorism, and their analogues in other areas of knowledge. Arguing that these attempts at reductive analysis have invariably failed, John L. Pollock defends an alternative theory of conceptual analysis in this book. The author suggests that concepts should be analyzed in terms of their justification conditions rather than their truth conditions. After laying a theoretical foundation for this alternative scheme of analysis, Professor Pollock applies his theory in proposing solutions to a number of traditional epistemological problems. Among the areas of knowledge discussed are perception, knowledge of the past, induction, knowledge of other minds, and a priori knowledge. Originally published in 1975. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
(source: Nielsen Book Data)

• Plans and resource-bounded practical reasoning, Michael E. Bratman et al
• cross domain inference and problem embedding, Robert Cummins
• the foundations of psychology, Jon Doyle
• memory, reason, and time - the step-logic approach, Jennifer J. Elgot-Drapkin et al
• artificial intelligence and hard problems - the expected complexity of problem solving, Clark Glymour et al
• normative and descriptive ideals, Henry Kyburg
• ampliative inference, computation, and dialectic, R. P. Loui
• probabilistic semantics for nonmonotonic reasoning, Judea Pearl
• Oscar - a general theory of rationality, John L. Pollock
• knowledge representation for natural-language competence, Stuart C. Shapiro and William J. Rapaport
• implementing the intentional stance, Yoav Shoham
• the dinosaur debate - explanatory coherence and the problem of competing hypotheses, Paul Thagard.
• (source: Nielsen Book Data)

Philosophers have found that the concepts and technology of artificial intelligence provide useful ways to test theories of knowledge and reason. Conversely, researchers in artificial intelligence, noting that the production of information processing systems requires a priori theory of rationality, have begun writing philosophy. "Philosophy and AI" presents invited contributions that focus on the different perspectives and techniques that philosophy and AI bring to the theory of rationality.
(source: Nielsen Book Data)