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Thinking in Complexity
This new edition also treats smart materials and artificial life. A new chapter on information and computational dynamics takes up many recent discussions in the community.
Thinking in Complexity
Complexity and nonlinearity are prominent features in the evolution of matter, life, and human society. Even our mind seems to be governed by the nonlinear dynamics of the complex networks in our brain. This book considers complex systems in the physical and biological sciences, cognitive and computer sciences, social and economic sciences, and philosophy and history of science. An in terdisciplinary methodology is introduced to explain the emergence of order in nature and mind and in the econ omy and society by common principles. These methods are sometimes said to foreshadow the new sciences of complexity characterizing the scientific deve10pment of the 21 st century. The book critically an alyzes the successes and limits of this approach, its sys tematic foundations, and its historical and philosophical background. An epilogue discusses new standards of eth ical behavior which are demanded by the complex prob lems of nature and mind, economy and society.
Artificial intelligence - When do machines take over?
Everybody knows them. Smartphones that talk to us, wristwatches that record our health data, workflows that organize themselves automatically, cars, airplanes and drones that control themselves, traffic and energy systems with autonomous logistics or robots that explore distant planets are technical examples of a networked world of intelligent systems. Machine learning is dramatically changing our civilization. We rely more and more on efficient algorithms, because otherwise we will not be able to cope with the complexity of our civilizing infrastructure. But how secure are AI algorithms? This challenge is taken up in the 2nd edition: Complex neural networks are fed and trained with huge amo...
Symmetries of Nature
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The Universe as Automaton
This Brief is an essay at the interface of philosophy and complexity research, trying to inspire the reader with new ideas and new conceptual developments of cellular automata. Going beyond the numerical experiments of Steven Wolfram, it is argued that cellular automata must be considered complex dynamical systems in their own right, requiring appropriate analytical models in order to find precise answers and predictions in the universe of cellular automata. Indeed, eventually we have to ask whether cellular automata can be considered models of the real world and, conversely, whether there are limits to our modern approach of attributing the world, and the universe for that matter, essentially a digital reality.
Complexities of Production and Interacting Human Behaviour
As the real world is rapidly becoming more and more complicated, economists need to venture beyond the boundaries of mainstream economics and integrate philosophical thought and complexity into their analytical frameworks. In this context, this volume brings together papers on economic theory and its related issues, exploring complex production systems and heterogeneously interacting human behavior. The author challenges economists to integrate economic theory and moral science anew by referring to evolutionary economics and socio-econophysics. The three parts of the book focus on the complexities of production and social interaction, the moral science of heterogeneous economic interaction, and the Avatamsaka’s dilemma of the two-person game with only positive spillovers.
Organic Computing
In this book, the major ideas behind Organic Computing are delineated, together with a sparse sample of computational projects undertaken in this new field. Biological metaphors include evolution, neural networks, gene-regulatory networks, networks of brain modules, hormone system, insect swarms, and ant colonies. Applications are as diverse as system design, optimization, artificial growth, task allocation, clustering, routing, face recognition, and sign language understanding.
From Summetria to Symmetry: The Making of a Revolutionary Scientific Concept
Many literary critics seem to think that an hypothesis about obscure and remote questions of history can be refuted by a simple demand for the production of more evidence than in fact exists. The demand is as easy to make as it is impossible to satisfy. But the true test of an hypothesis, if it cannot be shown to con?ict with known truths, is the number of facts that it correlates and explains. Francis M. Cornford [1914] 1934, 220. It was in the autumn of 1997 that the research project leading to this publication began. One of us [GH], while a visiting fellow at the Center for Philosophy of Science (University of Pittsburgh), gave a talk entitled, “Proportions and Identity: The Aesthetic A...
Extending the Evolutionary Synthesis
The theory of evolution is itself evolving with new findings and changes in the fundamental underlying concepts. It is true that today's synthetic theory, which goes back to Darwin, is persistently successful. However, it offers no convincing explanation to many questions, some examples of which are as follows: What forms of inheritance exist besides genetics; how complex variations, especially evolutionary innovations such as bird feathers and turtle shells, arise; how the environment affects the evolution of species and is changed by them simultaneously; and why the evolution of birds, corals, and human culture is not explainable by natural selection alone. Scientific findings of the last ...
