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Models And Methods In The Philosophy Of Science Book

Models And Methods In The Philosophy Of Science
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  • Models And Methods In The Philosophy Of Science
  • Written by author Patrick Suppes
  • Published by Springer-Verlag New York, LLC, May 1993
  • This book publishes 31 of the author's selected papers which have appeared, with one exception, since 1970. The papers cover a wide range of topics in the philosophy of science. Part I is concerned with general methodology, including formal and axiomatic
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Preface
Pt. IGeneral Methodology1
1The Role of Formal Methods in the Philosophy of Science3
2The Study of Scientific Revolutions: Theory and Methodology15
3Limitations of the Axiomatic Method in Ancient Greek Mathematical Sciences25
4The Plurality of Science41
5Heuristics and the Axiomatic Method55
6Representation Theory and the Analysis of Structure67
Pt. IICausality and Explanation83
7Causal Analysis of Hidden Variables85
8Scientific Causal Talk95
9Explaining the Unpredictable111
10Conflicting Intuitions About Causality121
11When are Probabilistic Explanations Possible?141
12Non-Markovian Causality in the Social Sciences with Some Theorems on Transitivity149
Pt. IIIProbability and Measurement161
13Finite Equal-Interval Measurement Structures163
14The Measurement of Belief181
15The Logic of Clinical Judgment: Bayesian and Other Approaches201
16Arguments for Randomizing213
17Propensity Representations of Probability225
18Indeterminism or Instability, Does It Matter?247
Pt. IVPhysics259
19Descartes and the Problem of Action at a Distance261
20Some Open Problems in the Philosophy of Space and Time271
21Aristotle's Concept of Matter and Its Relation to Modern Concepts of Matter289
22Popper's Analysis of Probability in Quantum Mechanics311
23Probabilistic Causality in Quantum Mechanics327
Pt. VPsychology339
24From Behaviorism to Neobehaviorism341
25Learning Theory for Probabilistic Automata and Register Machines, with Applications to Educational Research357
26Is Visual Space Euclidean?373
27Davidson's Views on Psychology as a Science395
28Current Directions in Mathematical Learning Theory407
29On Deriving Models in the Social Sciences435
30The Principle of Invariance with Special Reference to Perception451
31Can Psychological Software be Reduced to Physiological Hardware?471
Bibliography483
Author Index507


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