Patrick Suppes: Scientific Philosopher: Volume 1: Probability and Probabilistic Causality Volume 2: Philosophy of Physics, Theory Structure and Measurement ... and Action Theory (Synthese Library)

Book Description

Patrick Suppes is a philosopher and scientist whose contributions range over probability and statistics, mathematical and experimental psychology, the foundations of physics, education theory, the philosophy of language, measurement theory, and the philosophy of science. He has also been a pioneer in the area of computer assisted instruction. In each of these areas, Suppes has provided seminal ideas that in some cases led to shaping the direction of research in the field. The papers contained in this collection were commissioned with the mandate of advancing research in their respective fields rather than retrospectively surveying the contributions that Suppes himself has made. The authors form an interesting mixture of researchers in both formal philosophy of science and science itself all of whom have been inspired by his ideas. To maintain the spirit of constructive dialogue that characterizes Suppes's intellectual style, he has written individual responses to each article.

In Volume 1: Probability and Probabilistic Causality, nineteen distinguished philosophers and scientists focus their attention on probabilistic issues. In Part I the contributors explore axiomatic representations of probability theory including qualitative and interval valued probabilities as well as traditional point valued probabilities. Belief structures and the dynamics of belief are also treated in detail. In Part II the rapidly growing field of probabilistic causation is assessed from both formal and empirical viewpoints.
For probability theorists, statisticians, economists, philosophers of science, psychologists and those interested in the foundations of mathematical social science.

In Volume 2: Philosophy of Physics, Theory Structure, and Measurement Theory, fifteen distinguished philosophers and scientists cover a wide variety of topics. Part III covers issues in quantum theory, geometry, classical mechanics, and computational physics. Part IV explores Suppes's well known set-theoretic account of scientific theories which has served him well throughout his career. Suppes's contributions to measurement theory have been widely used in mathematical psychology and elsewhere, and this material is the subject of Part V.
For physicists, logicians, workers in mathematical social sicence, and philosophers of science.

In Volume 3: Philosophy of Language and Logic, Learning and Action Theory, fourteen distinguished philosophers and scientists explore issues in the philosophy of language, logic, and philosophical psychology. Suppes's suggestions that quantum theory requires a rethinking of classical logic form a particularly sharp account of that controversial thesis, and Part VI deals with this issue together with topics in the philosophy of language and logic, including relational grammars and anaphora. Part VII deals with issues in psychology, action theory, and robotics, while Part VIII concludes with a general survey of Suppes's views in the philosophy of science. A comprehensive chronological and topical bibliography of Suppes's writings is included in this volume.
For philosophers of language, theoretical linguists, logicians, workers in mathematical social sciences, and philosophers of science.

Orthomodular Structures as Quantum Logics: Intrinsic Properties, State Space and Probabilistic Topics (Fundamental Theories of Physics)

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Orthomodular Structures as Quantum Logics: Intrinsic Properties, State Space and Probabilistic Topics (Fundamental Theories of Physics)
Pavel Pták , and Sylvia Pulmannová
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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ASIN: 0792312074

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Probabilistic Theory of Structures
Isaac Elishakoff
Manufacturer: Dover Publications
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Binding: Paperback

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Stochastic Finite Elements: A Spectral Approach
An Introduction to Random Vibrations, Spectral & Wavelet Analysis: Third Edition
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Methods of Structural Safety
Probability, Reliability And Statistical Methods In Engineering Design

ASIN: 0486406911

Book Description

Well-written introduction covers the elements of the theory of probability from two or more random variables, the reliability of such multivariable structures, the theory of random function, Monte Carlo methods of treating problems incapable of exact solution, and more. No previous knowledge of the subject necessary. Numerous examples, illustrative figures.

Customer Reviews:

Well worth the price.......2003-06-26

A nice, interesting book with a lot of useful information on probabilistic structural analysis, but does not follow the current industrial practice that is leaning towards stochastic FEA and FORM/SORM based limit state analysis. If you want to understand modern structural reliability theory, or plan to work in probabiistic design, I would strongly reccomend the textbooks by Haldar & Mahadevan. In short, Prof. Elishakoff's book will be a nice companion volume, but not a main reference. Cant beat the price, though.

Review.......2000-09-04

This book is a very lucidly written one in the area of probabilitistic applications in mechanics and vibratrions. The first chapter is an introduction in to the history of probability and its roots. The book begins with an introduction to probability and probability distributions and this is covered in the initial couple of chapters. The second chapter deals with the basics of probability involving set thory. The third and fourth chapters deals with the basic concepts of probability and deals with different probability distributions in practice. In the next couple of chapters the concepts of derived distributions are covered. The concept of derived distributions along with transformations used are covered in the fourth and fifth chapters. The theory of random functions are covered in the sixth chapter. Then the application of probability and stochastic processes to structural mechanics for example stability, vibration theory have been covered. The final chapter is on the random number generation. It deals with Monte Carlo simulation of probability distributions and random functions.

Dynamic Probabilistic Models and Social Structure: Essays on Socioeconomic Continuity (Theory and Decision Library B:)

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Dynamic Probabilistic Models and Social Structure: Essays on Socioeconomic Continuity (Theory and Decision Library B:)
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Book Description

This monograph deals with the application of stochastic analysis and control techniques to the study of socioeconomic problems arising in processes of development and growth. Economic issues are formulated in a manner amenable to rigorous mathematical scrutiny without losing sight of their essential content.
This self-contained work consists of three parts. Part I is a detailed examination of basic themes of available theories of political economy and develops a body of theoretical tools appropriate to the investigation of stochastic accumulation of capital within the framework of social reproduction.
Part II points to the elaboration of a novel approach using probabilistic and variational methods. Key concepts such as expansion of capacity, development of productive forces, generation of economic surplus and effective demand are incorporated in stochastic models where learning, renewal of system potentials and conflicting social arrangements are at the heart of capital accumulation.
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Genetic Algorithms + Data Structures = Evolution Programs (Artificial Intelligence)

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Lot of ideas for Genetic and Evolutionary Algorithm
could GA get possibly any eaiser to understand???
One of the best book on genetic algorithms
pretty bad
Awful, unreadable book.

Genetic Algorithms + Data Structures = Evolution Programs (Artificial Intelligence)
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Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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Amazon.com

Zbigniew Michalewicz's Genetic Algorithms + Data Structures = Evolution Programs has three sections. The first section is a straightforward introduction to genetic algorithms. In the second section, Michalewicz describes how to apply genetic algorithms to numerical optimization. Michalewicz, who is a pioneer in this field, discusses the rationale for using genetic algorithms for numerical optimization and describes several experiments that show how this new type of genetic algorithm performs. The author devotes the third section of the book to evolution programs.

Book Description

This book discusses a class of algorithms which rely on analogies to natural processes - algorithms based on the principle of evolution, i.e., survival of the fittest. In these algorithms, called evolution programs, a population of individuals undergo a sequence of transformations. The individuals strive for survival: a selection scheme biased towards fitter individuals selects the next generation. After some generations, the program converges and the best individual hopefully represents the optimum solution. Hence evolution programming techniques are applicable to various hard optimization problems. The book discusses constrained optimization problems in the areas of optimal control, operations research, and engineering. The problems include optimization of functions with linear constraints, the traveling salesman problem, scheduling and partitioning problems, etc. All methods are illustrated by results obtained from various experimental systems. The book collects, in a unified and comprehensive manner, the results of evolution programming techniques previously available only in widely scattered research papers. The importance of these techniques has been growing in the last decade, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only prerequisite is basic undergraduate mathematics. It is aimed at researchers, practitioners, and graduate students in the areas of computer science (especially artificial intelligence), operations research, and engineering.

Customer Reviews:

Lot of ideas for Genetic and Evolutionary Algorithm.......2007-01-05

This book is not written to be the primary text book for a Genetic Algotithm, Data Structure or a Neural Algorithm course. However this book gives an excellent introduction to modern approaches to Evolutionary Algorithm, and how/whether GAs and EAa can be applied successfully to problems of Optimisation, Navigation, and also other contemporary and emerging fields.

This book emphasizes on a lot of fresh ideas (which already requires background in GA, and Algorithms) and may be highly recommended for reference reading of Evolutionary Algorithms and allied Techniques.

could GA get possibly any eaiser to understand???.......2005-03-20

I saw this book once with one of my buddies,and read the first chapter,,,it was after looking up the first chapter i decided to buy it...I have read some other books on this topic,and since i was kinda in rush for a project which needed GA,i found no other book which explains the concepts and procedures, this straightforward and "right to the point".As far as writing this book goes, "Michalewicz" has done a really really great job.
Go for it guys!!!
cheers,
Amir

One of the best book on genetic algorithms.......2002-07-12

A very good vision of the evolutionary optimisation techniques not only GA. As well there is an excellent chapter on constraints handling. Maybe it is not one of the easiest book on GA but it is definitely the most useful.

pretty bad.......2001-06-13

I agree with the previous reviewer: books should be clear and get to the point. Forget about this one. Get Michalewicz and Fogel's "How to solve it" book. It is MUCH better than this one in all levels: it is better written and the content is more authorative and helpful to novices and experts.

This book is supposed to be a textbook. Maybe that's why it sells so well. I guess I am lucky I didn't have to take a class with this thing.

Awful, unreadable book........2000-11-14

This man needs to invest in a good editor. Many times I'd read through half a page or so, stop to think about it and then rephrase it into one or two sentences. Blobs of math appear to be thrown in with little justification, and the book isn't improved by them.

But this book is not only unreadable, it's also not useful. It's more an overview of the area than anything else; it doesn't give adequate information about genetic programming or neural networks. It skims many areas in a close to incomprehensible fashion without covering any in what I would consider to be good detail.

Finally, I'm not dim. I have a PhD myself and am used to ploughing through gibberish. But save your money and don't buy this book (Unless you have a wobbly table that needs fixing).

Logarithmic Combinatorial Structures: A Probabilistic Approach (EMS Monographs in Mathematics)
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Logarithmic Combinatorial Structures: A Probabilistic Approach (EMS Monographs in Mathematics)
Richard Arratia , A.D. Barbour , and Simon Tavare
Manufacturer: European Mathematical Society
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The elements of many classical combinatorial structures can be naturally decomposed into components. Permutations can be decomposed into cycles, polynomials over a finite field into irreducible factors, mappings into connected components. In all of these examples, and in many more, there are strong similarities between the numbers of components of different sizes that are found in the decompositions of "typical" elements of large size. For instance, the total number of components grows logarithmically with the size of the element, and the size of the largest component is an appreciable fraction of the whole. This book explains the similarities in asymptotic behavior as the result of two basic properties shared by the structures: the conditioning relation and the logarithmic condition. The discussion is conducted in the language of probability, enabling the theory to be developed under rather general and explicit conditions; for the finer conclusions, Stein's method emerges as the key ingredient. The book is thus of particular interest to graduate students and researchers in both combinatorics and probability theory. Distributed within the Americas by the American Mathematical Society.

Probabilistic Conditional Independence Structures (Information Science and Statistics)

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Probabilistic Conditional Independence Structures (Information Science and Statistics)
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Quantam Independent Increment Processes II: Structure of Quantun Levy Pocesses, Classical Probability, and Physics (Lecture Notes in Mathematics)

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Quantam Independent Increment Processes II: Structure of Quantun Levy Pocesses, Classical Probability, and Physics (Lecture Notes in Mathematics)
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