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Author: William Bechtel Publisher: MIT Press ISBN: 0262514737 Category : Science Languages : en Pages : 341
Book Description
An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993.
Author: William Bechtel Publisher: MIT Press ISBN: 0262514737 Category : Science Languages : en Pages : 341
Book Description
An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993.
Author: Paul Milgrom Publisher: Columbia University Press ISBN: 023154457X Category : Business & Economics Languages : en Pages : 222
Book Description
Traditional economic theory studies idealized markets in which prices alone can guide efficient allocation, with no need for central organization. Such models build from Adam Smith’s famous concept of an invisible hand, which guides markets and renders regulation or interference largely unnecessary. Yet for many markets, prices alone are not enough to guide feasible and efficient outcomes, and regulation alone is not enough, either. Consider air traffic control at major airports. While prices could encourage airlines to take off and land at less congested times, prices alone do just part of the job; an air traffic control system is still indispensable to avoid disastrous consequences. With just an air traffic controller, however, limited resources can be wasted or poorly used. What’s needed in this and many other real-world cases is an auction system that can effectively reveal prices while still maintaining enough direct control to ensure that complex constraints are satisfied. In Discovering Prices, Paul Milgrom—the world’s most frequently cited academic expert on auction design—describes how auctions can be used to discover prices and guide efficient resource allocations, even when resources are diverse, constraints are critical, and market-clearing prices may not even exist. Economists have long understood that externalities and market power both necessitate market organization. In this book, Milgrom introduces complex constraints as another reason for market design. Both lively and technical, Milgrom roots his new theories in real-world examples (including the ambitious U.S. incentive auction of radio frequencies, whose design he led) and provides economists with crucial new tools for dealing with the world’s growing complex resource-allocation problems.
Author: Allen B. Downey Publisher: "O'Reilly Media, Inc." ISBN: 1449331696 Category : Computers Languages : en Pages : 159
Book Description
Expand your Python skills by working with data structures and algorithms in a refreshing context—through an eye-opening exploration of complexity science. Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations. You’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise. Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tables Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get starter code and solutions to help you re-implement and extend original experiments in complexity Explore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topics Examine case studies of complex systems submitted by students and readers
Author: G. Nicolis Publisher: W H Freeman & Company ISBN: 9780716718598 Category : Science Languages : en Pages : 313
Book Description
Unexpected discoveries in nonequilibrium physics and nonlinear dynamics are changing our understanding of complex phenomena. Recent research has revealed fundamental new properties of matter in far-from-equilibrium conditions, and the prevalence of instability-where small changes in initial conditions may lead to amplified effects.
Author: A. Hoerbst Publisher: IOS Press ISBN: 1614996784 Category : Health & Fitness Languages : en Pages : 852
Book Description
The field of health is an increasingly complex and technical one; and an area in which a more multidisciplinary approach would undoubtedly be beneficial in many ways. This book presents papers from the conference ‘Health – Exploring Complexity: An Interdisciplinary Systems Approach’, held in Munich, Germany, from August 28th to September 2nd 2016. This joint conference unites the conferences of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), the German Society for Epidemiology (DGEpi), the International Epidemiological Association - European Region, and the European Federation for Medical Informatics (EFMI). These societies already have long-standing experience of integrating the disciplines of medical informatics, biometry, epidemiology and health data management. The book contains over 160 papers, and is divided into 14 sections covering subject areas such as: health and clinical information systems; eHealth and telemedicine; big data and advanced analytics; and evidence-based health informatics, evaluation and education, among many others. The book will be of value to all those working in the field of health and interested in finding new ways to enable the collaboration of different scientific disciplines and the establishment of comprehensive methodological approaches.
Author: Craig Hill Publisher: Springer ISBN: 9400755481 Category : Science Languages : en Pages : 247
Book Description
Complexity occurs in biological and synthetic systems alike. This general phenomenon has been addressed in recent publications by investigators in disciplines ranging from chemistry and biology to psychology and philosophy. Studies of complexity for molecular scientists have focussed on breaking symmetry, dissipative processes, and emergence. Investigators in the social and medical sciences have focused on neurophenomenology, cognitive approaches and self-consciousness. Complexity in both structure and function is inherent in many scientific disciplines of current significance and also in technologies of current importance that are rapidly evolving to address global societal needs. Several of these multifaceted scientific disciplines are addressed in this book including complexity from the general and philosophical perspective, magnetic phenomena, control of self assembly and function in large multicomponent clusters, application of theory to probe structure and mechanism in highly complex molecular species, and the design of multifunctional nanoscale molecules of value in decontamination and solar fuels research. Each chapter is both a review and addresses some ongoing challenges, thus each should provide a good preparation for further work in these highly active areas of research endeavour.
Author: Michael R. Lissack Publisher: Bloomsbury Publishing USA ISBN: 0313013942 Category : Business & Economics Languages : en Pages : 326
Book Description
What is complexity science? What is management? And how are the two linked? The potential of complexity science in the fields of management and organization studies has been explored before, yet there is little agreement on what complexity science truly is. Lissack and Rivkin, along with a panel of distinguished academics and executives, identify critical topics in the study of complexity science. They reveal complexity science to be a process, one seeking and understanding of the systems we inhabit, and ways of applying that understanding to the management of organizations. Complexity science is not a management fad, and the authors do not treat it as such. Instead, they offer useful and fascinating viewpoints on how work is managed in an age of business uncertainty, and how it can be more successfully managed with the aid of this rapidly evolving new field of science. Their multidisciplinary book combines systems theory, statistical modeling, and individual and organizational learning in an innovative new context. The volume takes a pragmatic approach: if it works, it's right. And complexity science, say the authors, work extremely well. This book is an important resource for upper level executives, specialists in organizational behavior, and their colleagues in the academic community.
Author: Ton Jörg Publisher: Springer Science & Business Media ISBN: 9400713037 Category : Social Science Languages : en Pages : 326
Book Description
The underlying idea and motive for the book is that the notion of complexity may humanize the social sciences, may conceive the complex human being as more human, and turn reality as assumed in our doing social science into a more complex, that is a richer reality for all. The main focus of this book is on new thinking in complexity, with complexity to be taken as derived from the Latin word complexus: ‘that which is interwoven.’ The trans-disciplinary approach advocated here will be trans-disciplinary in two ways: firstly, by going beyond the separate disciplines within the fields of both natural sciences and social sciences, and, secondly, by going beyond the separate cultures of the natural sciences and of the social sciences and humanities.
Author: William Bechtel
Author: William Bechtel
Author: Paul Milgrom
Author: Allen B. Downey
Author: G. Nicolis
Author: Alex Hagan
Author: A. Hoerbst
Author: George V. Coyne
Author: Craig Hill
Author: Michael R. Lissack
Author: Ton Jörg