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On January 20th, 22nd, and 29th, 1970 Saul Kripke delivered three
lectures at Princeton University. They produced something of a
sensation. In the lectures he argued, amongst other things, that
many names in ordinary language referred to objects directly rather
than by means of associated descriptions; that causal chains from
language user to language user were an important mechanism for
preserving reference; that there were necessary a posteriori and
contingent a priori truths; that identity relations between rigid
designators were necessary; and argued, more tentatively, that
materialist identity theories in the philosophy of mind were
suspect. Interspersed with this was a consider able amount of
material on natural kind terms and essentialism. As a result of
these lectures and a related 1971 paper, 'Identity and Necessity'
(Kripke [1971]), talk of rigid designators, Hesperus and
Phosphorus, meter bars, gold and H 0, and suchlike quickly became
commonplace in philosophical circles 2 and when the lectures were
published under the title Naming and Necessity in the collection
The Semantics of Natural Language (Davidson and Harman l [1972]),
that volume became the biggest seller in the Reidel (later Kluwer)
list. The cluster of theses surrounding the idea that a relation of
direct reference 2 exists between names and their referents is now
frequently referred to as 'The 3 New Theory of Reference'.
On January 20th, 22nd, and 29th, 1970 Saul Kripke delivered three
lectures at Princeton University. They produced something of a
sensation. In the lectures he argued, amongst other things, that
many names in ordinary language referred to objects directly rather
than by means of associated descriptions; that causal chains from
language user to language user were an important mechanism for
preserving reference; that there were necessary a posteriori and
contingent a priori truths; that identity relations between rigid
designators were necessary; and argued, more tentatively, that
materialist identity theories in the philosophy of mind were
suspect. Interspersed with this was a consider able amount of
material on natural kind terms and essentialism. As a result of
these lectures and a related 1971 paper, 'Identity and Necessity'
(Kripke [1971]), talk of rigid designators, Hesperus and
Phosphorus, meter bars, gold and H 0, and suchlike quickly became
commonplace in philosophical circles 2 and when the lectures were
published under the title Naming and Necessity in the collection
The Semantics of Natural Language (Davidson and Harman l [1972]),
that volume became the biggest seller in the Reidel (later Kluwer)
list. The cluster of theses surrounding the idea that a relation of
direct reference 2 exists between names and their referents is now
frequently referred to as 'The 3 New Theory of Reference'.
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 interest from classical problems in the
philosophy of mind and philosophical psychology through issues in
cognitive psychology and sociobiology (concerning the mental powers
of other species) to ideas related to artificial intelligence and
computer science. While primary emphasis will be placed upon
theoretical, conceptual, and epistemological aspects of these
problems and domains, empirical, experimen tal, and methodological
studies will also appear from time to time. The present volume
reflects the kind of insights that can be obtained when research
workers in philosophy, artificial intelligence, and computer
science explore problems of common concern. The issues here tend to
fall into two broad but varied sets, namely: those concerned with
content and concepts, on the one hand, and those concerned with
semantics and epistemology, on the other. The collection begins
with a prologue that focuses upon the relations between
connectionism and alternative conceptions of nativism and ends with
an epilogue that examines the significance of alternative
conceptions of the Frame Problem for artificial intelligence.
Because these papers are rich and diverse, they ought to appeal to
a wide and heterogeneous audience. J.H.F."
Among the most important problems confronting computer science is
that of developing a paradigm appropriate to the discipline.
Proponents of formal methods - such as John McCarthy, C.A.R. Hoare,
and Edgar Dijkstra - have advanced the position that computing is a
mathematical activity and that computer science should model itself
after mathematics. Opponents of formal methods - by contrast,
suggest that programming is the activity which is fundamental to
computer science and that there are important differences that
distinguish it from mathematics, which therefore cannot provide a
suitable paradigm. Disagreement over the place of formal methods in
computer science has recently arisen in the form of renewed
interest in the nature and capacity of program verification as a
method for establishing the reliability of software systems. A
paper that appeared in Communications of the ACM entitled, Program
Verification: The Very Idea', by James H. Fetzer triggered an
extended debate that has been discussed in several journals and
that has endured for several years, engaging the interest of
computer scientists (both theoretical and applied) and of other
thinkers from a wide range of backgrounds who want to understand
computer science as a domain of inquiry. The editors of this
collection have brought together many of the most interesting and
important studies that contribute to answering questions about the
nature and the limits of computer science. These include early
papers advocating the mathematical paradigm by McCarthy, Naur, R.
Floyd, and Hoare (in Part I), others that elaborate the paradigm by
Hoare, Meyer, Naur, and Scherlis and Scott (in Part II),
challenges, limits and alternatives explored by C. Floyd, Smith,
Blum, and Naur (in Part III), and recent work focusing on formal
verification by DeMillo, Lipton, and Perlis, Fetzer, Cohn, and
Colburn (in Part IV). It provides essential resources for further
study. This volume will appeal to scientists, philosophers, and
laypersons who want to understand the theoretical foundations of
computer science and be appropriately positioned to evaluate the
scope and limits of the discipline.
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 psychology through issues in
cognitive psychology and sociobiology (concerning the mental
capabilities of other species) to ideas related to artificial
intelligence and to computer science. While primary emphasis will
be placed upon theoretical, conceptual and epistemological aspects
of these problems and domains, empirical, experimental and
methodological studies will also appear from time to time. The
present volume illustrates the approach represented by this series.
It addresses fundamental questions lying at the heart of artificial
intelligence, including those of the relative virtues of
computational and of non-computational conceptions of language and
of mind, whether AI should be envisioned as a philosophical or as a
scientific discipline, the theoretical character of patterns of
inference and modes of argumenta tion (especially, defeasible and
inductive reasoning), and the relations that may obtain between AI
and epistemology. Alternative positions are developed in detail and
subjected to vigorous debate in the justifiable expectation that -
here as elsewhere - critical inquiry provides the most promising
path to discovering the truth about ourselves and the world around
us. lH.F."
With this defense of intensional realism as a philosophical
foundation for understanding scientific procedures and grounding
scientific knowledge, James Fetzer provides a systematic
alternative to much of recent work on scientific theory. To Fetzer,
the current state of understanding the 'laws' of nature, or the
'law-like' statements of scientific theories, appears to be one of
philosophical defeat; and he is determined to overcome that defeat.
Based upon his incisive advocacy of the single-case propensity
interpretation of probability, Fetzer develops a coherent structure
within which the central problems of the philosophy of science find
their solutions. Whether the reader accepts the author's
contentions may, in the end, depend upon ancient choices in the
interpretation of experience and explanation, but there can be
little doubt of Fetzer's spirited competence in arguing for setting
ontology before epistemology, and within the analysis of language.
To us, Fetzer's ambition is appealing, fusing, as he says, the
substantive commitment of the Popperian with the conscientious
sensitivity of the Hempelian to the technical precision required
for justified explication. To Fetzer, science is the objective
pursuit of fallible general knowledge. This innocent character
ization, which we suppose most scientists would welcome, receives a
most careful elaboration in this book; it will demand equally
careful critical con sideration. Center for the Philosophy and
ROBERT S. COHEN History of Science, MARX W. WARTOFSKY Boston
University October 1981 v TABLE OF CONTENTS EDITORIAL PREFACE v
FOREWORD xi ACKNOWLEDGEMENTS xv PART I: CAUSATION 1."
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 psychology through issues in
cognitive psychology and sociobiology (concerning the mental
capabilities of other species) to ideas related to artificial
intelligence and computer science. While primary emphasis will be
placed upon theoretical, conceptual, and epistemological aspects of
these problems and domains, empirical, experimental, and
methodological studies will also appear from time to time. No
problem within the field of cognitive inquiry is more difficult
than that of developing an adequate conception of the nature of
mind and of its mode of operation. Our purpose in compiling the
present volume has been to contribute to the pursuit of this
objective by bringing together a repre sentative cross-section of
the principal approaches and the primary players who are engaged in
contemporary debate on these crucial issues. The book begins with a
comprehensive introduction composed by David Cole, the senior
editor of this work, which provides a background for understanding
the major problems and alternative solutions, and ends with a
selected bibliography intended to promote further research. If our
efforts assist others in dealing with these issues, they will have
been worthwhile. J. H. F. David J. Cole et at. (eds. ), Philosophy,
Mind, and Cognitive Inquiry, ix."
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."
The papers presented in this special collection focus upon
conceptual, the oretical and epistemological aspects of
sociobiology, an emerging discipline that deals with the extent to
which genetic factors influence or control patterns of behavior as
well as the extent to which patterns of behavior, in turn,
influence or control genetic evolution. The Prologue advances a
compre hensive acco/unt of the field of gene-culture co-evolution,
where Lumsden and Gushurst differentiate between "classical"
sociobiology (represented especially by Wilson's early work) and
current research on human socio biology (represented by Lumsden and
Wilson's later work), which emphasizes interplay between genes,
minds, and culture. The specter of genetic deter minism, no doubt,
has created considerable controversy, some of which may be laid to
rest by Hanna's analysis of the (ambiguous) notion of a "genetic
program," which indicates the necessity for distinguishing between
descriptive and prescriptive dimensions of this complex concept.
Brandon offers a framework for assessing the respective
contributions of nature and of nurture by advancing a means for
measuring genetic and cultural influences upon "inheritance," which
supports the conclusion that evolving patterns of behavior do not
always maximize inclusive fitness, contrary to what socio
biologists have claimed. The influence of culture upon genetic
evolution, of course, can be adequately appraised only when a
suitable account of culture itself has been found, a desideratum
Smillie attempts to satisfy by utilizing the notion of "cinfo" as
culturally transmitted ecological informa tion, a resource other
species tend not to exploit."
Among the most important problems confronting computer science is
that of developing a paradigm appropriate to the discipline.
Proponents of formal methods - such as John McCarthy, C.A.R. Hoare,
and Edgar Dijkstra - have advanced the position that computing is a
mathematical activity and that computer science should model itself
after mathematics. Opponents of formal methods - by contrast,
suggest that programming is the activity which is fundamental to
computer science and that there are important differences that
distinguish it from mathematics, which therefore cannot provide a
suitable paradigm. Disagreement over the place of formal methods in
computer science has recently arisen in the form of renewed
interest in the nature and capacity of program verification as a
method for establishing the reliability of software systems. A
paper that appeared in Communications of the ACM entitled, Program
Verification: The Very Idea', by James H. Fetzer triggered an
extended debate that has been discussed in several journals and
that has endured for several years, engaging the interest of
computer scientists (both theoretical and applied) and of other
thinkers from a wide range of backgrounds who want to understand
computer science as a domain of inquiry. The editors of this
collection have brought together many of the most interesting and
important studies that contribute to answering questions about the
nature and the limits of computer science. These include early
papers advocating the mathematical paradigm by McCarthy, Naur, R.
Floyd, and Hoare (in Part I), others that elaborate the paradigm by
Hoare, Meyer, Naur, and Scherlis and Scott (in Part II),
challenges, limits and alternatives explored by C. Floyd, Smith,
Blum, and Naur (in Part III), and recent work focusing on formal
verification by DeMillo, Lipton, and Perlis, Fetzer, Cohn, and
Colburn (in Part IV). It provides essential resources for further
study. This volume will appeal to scientists, philosophers, and
laypersons who want to understand the theoretical foundations of
computer science and be appropriately positioned to evaluate the
scope and limits of the discipline.
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 interest from classical problems in the
philosophy of mind and philosophical psychology through issues in
cognitive psychology and sociobiology (concerning the mental powers
of other species) to ideas related to artificial intelligence and
computer science. While primary emphasis will be placed upon
theoretical, conceptual, and epistemological aspects of these
problems and domains, empirical, experimen tal, and methodological
studies will also appear from time to time. The present volume
reflects the kind of insights that can be obtained when research
workers in philosophy, artificial intelligence, and computer
science explore problems of common concern. The issues here tend to
fall into two broad but varied sets, namely: those concerned with
content and concepts, on the one hand, and those concerned with
semantics and epistemology, on the other. The collection begins
with a prologue that focuses upon the relations between
connectionism and alternative conceptions of nativism and ends with
an epilogue that examines the significance of alternative
conceptions of the Frame Problem for artificial intelligence.
Because these papers are rich and diverse, they ought to appeal to
a wide and heterogeneous audience. J.H.F."
Science aims at the discovery of general principles of special
kinds that are applicable for the explanation and prediction of the
phenomena of the world in the form of theories and laws. When the
phenomena themselves happen to be general, the principlesinvolved
assume the form of theories; and when they are p- ticular, they
assume the form of general laws. Theories themselves are sets of
laws and de nitions that apply to a common domain, which makes laws
indispensable to science. Understanding science thus depends upon
understanding the nature of theories and laws, the logical
structure of explanations and predictions based upon them, and the
principles of inference and decision that apply to theories and
laws. Laws and theories can differ in their form as well as in
their content. The laws of quantum mechanics are indeterministic
(or probabilistic), for example, while those of classical mechanics
are deterministic (or universal) instead. The history of science re
ects an increasing role for probabilities as properties of the
world but also as measures of evidential support and as degrees of
subjective belief. Our purpose is to clarify and illuminate the
place of probability in science.
Science aims at the discovery of general principles of special
kinds that are applicable for the explanation and prediction of the
phenomena of the world in the form of theories and laws. When the
phenomena themselves happen to be general, the principlesinvolved
assume the form of theories; and when they are p- ticular, they
assume the form of general laws. Theories themselves are sets of
laws and de nitions that apply to a common domain, which makes laws
indispensable to science. Understanding science thus depends upon
understanding the nature of theories and laws, the logical
structure of explanations and predictions based upon them, and the
principles of inference and decision that apply to theories and
laws. Laws and theories can differ in their form as well as in
their content. The laws of quantum mechanics are indeterministic
(or probabilistic), for example, while those of classical mechanics
are deterministic (or universal) instead. The history of science re
ects an increasing role for probabilities as properties of the
world but also as measures of evidential support and as degrees of
subjective belief. Our purpose is to clarify and illuminate the
place of probability in science.
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 psychology through issues in
cognitive psychology and sociobiology (concerning the mental
capabilities of other species) to ideas related to artificial
intelligence and computer science. While primary emphasis will be
placed upon theoretical, conceptual, and epistemological aspects of
these problems and domains, empirical, experimental, and
methodological studies will also appear from time to time. No
problem within the field of cognitive inquiry is more difficult
than that of developing an adequate conception of the nature of
mind and of its mode of operation. Our purpose in compiling the
present volume has been to contribute to the pursuit of this
objective by bringing together a repre sentative cross-section of
the principal approaches and the primary players who are engaged in
contemporary debate on these crucial issues. The book begins with a
comprehensive introduction composed by David Cole, the senior
editor of this work, which provides a background for understanding
the major problems and alternative solutions, and ends with a
selected bibliography intended to promote further research. If our
efforts assist others in dealing with these issues, they will have
been worthwhile. J. H. F. David J. Cole et at. (eds. ), Philosophy,
Mind, and Cognitive Inquiry, ix."
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 phi losophical psychology through issues in
cognitive psychology and socio biology (concerning the mental
capabilities of other species) to ideas related to artificial
intelligence and computer science. While primary emphasis will be
placed upon theoretical, conceptual and epistemologi cal aspects of
these problems and domains, empirical, experimental and
methodological studies will also appear from time to time. Among
the most challenging and difficult projects within the scope of
artificial intelligence is the development and implementation of
com puter programs suitable for processing natural language. Our
purpose in compiling the present volume has been to contribute to
the foundations of this enterprise by bringing together classic
papers devoted to crucial problems involved in understanding
natural language, which range from issues of formal syntax and
logical form to those of possible-worlds and situation semantics.
The book begins with a comprehensive introduc tion composed by Jack
Kulas, the senior editor of this work, which pro vides a systematic
orientation to this complex field, and ends with a selected
bibliography intended to promote further research. If our efforts
assist others in dealing with these problems, they will have been
worthwhile. J. H. F."
An important collection of studies providing a fresh and original
perspective on the nature of mind, including thoughtful and
detailed arguments that explain why the prevailing paradigm - the
computational conception of language and mentality - can no longer
be sustained. An alternative approach is advanced, inspired by the
work of Charles S. Peirce, according to which minds are sign-using
(or semiotic') systems, which in turn generates distinctions
between different kinds of minds and overcomes problems that burden
more familiar alternatives. Unlike conceptions of minds as
machines, this novel approach has obvious evolutionary
implications, where differences in semiotic abilities tend to
distinguish the species. From this point of view, the scope and
limits of computer and AI systems can be more adequately appraised
and alternative accounts of consciousness and cognition can be more
thoroughly criticised. Readership: Intermediate and advanced
students of computer science, AI, cognitive science, and all
students of the philosophy of the mind.
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."
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 phi losophical psychology through issues in
cognitive psychology and socio biology (concerning the mental
capabilities of other species) to ideas related to artificial
intelligence and computer science. While primary emphasis will be
placed upon theoretical, conceptual and epistemologi cal aspects of
these problems and domains, empirical, experimental and
methodological studies will also appear from time to time. Among
the most challenging and difficult projects within the scope of
artificial intelligence is the development and implementation of
com puter programs suitable for processing natural language. Our
purpose in compiling the present volume has been to contribute to
the foundations of this enterprise by bringing together classic
papers devoted to crucial problems involved in understanding
natural language, which range from issues of formal syntax and
logical form to those of possible-worlds and situation semantics.
The book begins with a comprehensive introduc tion composed by Jack
Kulas, the senior editor of this work, which pro vides a systematic
orientation to this complex field, and ends with a selected
bibliography intended to promote further research. If our efforts
assist others in dealing with these problems, they will have been
worthwhile. J. H. F."
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 psychology through issues in
cognitive psychology and sociobiology (concerning the mental
capabilities of other species) to ideas related to artificial
intelligence and to computer science. While primary emphasis will
be placed upon theoretical, conceptual and epistemological aspects
of these problems and domains, empirical, experimental and
methodological studies will also appear from time to time. The
present volume illustrates the approach represented by this series.
It addresses fundamental questions lying at the heart of artificial
intelligence, including those of the relative virtues of
computational and of non-computational conceptions of language and
of mind, whether AI should be envisioned as a philosophical or as a
scientific discipline, the theoretical character of patterns of
inference and modes of argumenta tion (especially, defeasible and
inductive reasoning), and the relations that may obtain between AI
and epistemology. Alternative positions are developed in detail and
subjected to vigorous debate in the justifiable expectation that -
here as elsewhere - critical inquiry provides the most promising
path to discovering the truth about ourselves and the world around
us. lH.F."
The contributions to this special collection concern issues and
problems discussed in or related to the work of Wesley C. Salmon.
Salmon has long been noted for his important work in the philosophy
of science, which has included research on the interpretation of
probability, the nature of explanation, the character of reasoning,
the justification of induction, the structure of space/time and the
paradoxes of Zeno, to mention only some of the most prominent.
During a time of increasing preoccupation with historical and
sociological approaches to under standing science (which
characterize scientific developments as though they could be
adequately analysed from the perspective of political movements,
even mistaking the phenomena of conversion for the rational
appraisal of scientific theories), Salmon has remained stead fastly
devoted to isolating and justifying those normative standards
distinguishing science from non-science - especially through the
vindi cation of general principles of scientific procedure and the
validation of specific examples of scientific theories - without
which science itself cannot be (even remotely) adequately
understood. In this respect, Salmon exemplifies and strengthens a
splendid tradi tion whose most remarkable representatives include
Hans Reichenbach, Rudolf Carnap and Carl G. Hempel, all of whom
exerted a profound influence upon his own development."
The papers presented in this special collection focus upon
conceptual, the oretical and epistemological aspects of
sociobiology, an emerging discipline that deals with the extent to
which genetic factors influence or control patterns of behavior as
well as the extent to which patterns of behavior, in turn,
influence or control genetic evolution. The Prologue advances a
compre hensive acco/unt of the field of gene-culture co-evolution,
where Lumsden and Gushurst differentiate between "classical"
sociobiology (represented especially by Wilson's early work) and
current research on human socio biology (represented by Lumsden and
Wilson's later work), which emphasizes interplay between genes,
minds, and culture. The specter of genetic deter minism, no doubt,
has created considerable controversy, some of which may be laid to
rest by Hanna's analysis of the (ambiguous) notion of a "genetic
program," which indicates the necessity for distinguishing between
descriptive and prescriptive dimensions of this complex concept.
Brandon offers a framework for assessing the respective
contributions of nature and of nurture by advancing a means for
measuring genetic and cultural influences upon "inheritance," which
supports the conclusion that evolving patterns of behavior do not
always maximize inclusive fitness, contrary to what socio
biologists have claimed. The influence of culture upon genetic
evolution, of course, can be adequately appraised only when a
suitable account of culture itself has been found, a desideratum
Smillie attempts to satisfy by utilizing the notion of "cinfo" as
culturally transmitted ecological informa tion, a resource other
species tend not to exploit."
With this defense of intensional realism as a philosophical
foundation for understanding scientific procedures and grounding
scientific knowledge, James Fetzer provides a systematic
alternative to much of recent work on scientific theory. To Fetzer,
the current state of understanding the 'laws' of nature, or the
'law-like' statements of scientific theories, appears to be one of
philosophical defeat; and he is determined to overcome that defeat.
Based upon his incisive advocacy of the single-case propensity
interpretation of probability, Fetzer develops a coherent structure
within which the central problems of the philosophy of science find
their solutions. Whether the reader accepts the author's
contentions may, in the end, depend upon ancient choices in the
interpretation of experience and explanation, but there can be
little doubt of Fetzer's spirited competence in arguing for setting
ontology before epistemology, and within the analysis of language.
To us, Fetzer's ambition is appealing, fusing, as he says, the
substantive commitment of the Popperian with the conscientious
sensitivity of the Hempelian to the technical precision required
for justified explication. To Fetzer, science is the objective
pursuit of fallible general knowledge. This innocent character
ization, which we suppose most scientists would welcome, receives a
most careful elaboration in this book; it will demand equally
careful critical con sideration. Center for the Philosophy and
ROBERT S. COHEN History of Science, MARX W. WARTOFSKY Boston
University October 1981 v TABLE OF CONTENTS EDITORIAL PREFACE v
FOREWORD xi ACKNOWLEDGEMENTS xv PART I: CAUSATION 1."
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