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Complexity has received substantial attention from scientists and philosophers alike. There are numerous, often conflicting, accounts of how complexity should be defined and how it should be measured. Much less attention has been paid to the epistemic implications of complexity, especially in Ecology. How does the complex nature of ecological systems affect ecologists' ability to study them? This Element argues that ecological systems are complex in a rather special way: they are causally heterogeneous. Not only are they made up of many interacting parts, but their behaviour is variable across space or time. Causal heterogeneity is responsible for many of the epistemic difficulties that ecologists face, especially when making generalisations and predictions. Luckily, ecologists have the tools to overcome these difficulties, though these tools have historically been considered suspect by philosophers of science. The author presents an updated philosophical account with an optimistic outlook of the methods and status of ecological research.

Ecology --- Biocomplexity. --- Philosophy. --- Biological complexity --- Complexity, Biological --- Biology --- Biodiversity --- Ecophilosophy --- Complexity (Philosophy)

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Natural selection is more than the survival of the fittest: it is a force engendering higher biological complexity. Presenting a new explanation for the tendency of life to become more complex through evolution, this book offers an introduction to the key debates in evolutionary theory, including the role of genes and sex in evolution, the adaptive reasons for senescence and death and the origin of neural information. The author argues that biological complexity increased through the process of 'modularity transfer': modular phenotypes (proteins, somatic cells, learned behaviours) evolved into new modular information carriers (regulatory proteins, neural cells, words), giving rise to new information systems and higher levels of biological organisation. Modular Evolution makes sense of the unique place of humans in evolution, both as the pinnacle of biological complexity and inventors of non-biological evolution.

Evolution (Biology) --- Natural selection. --- Biocomplexity. --- Molecular evolution. --- Biochemical evolution --- Chemical evolution --- Evolution --- Life --- Molecular biology --- Biological complexity --- Complexity, Biological --- Biology --- Biodiversity --- Darwinism --- Selection, Natural --- Genetics --- Variation (Biology) --- Biological invasions --- Heredity --- Animal evolution --- Animals --- Biological evolution --- Evolutionary biology --- Evolutionary science --- Origin of species --- Biological fitness --- Homoplasy --- Natural selection --- Phylogeny --- Origin

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Experts from diverse fields, including artificial life, cognitive science, economics, developmental and evolutionary biology, and the arts, discuss modularity.Modularity--the attempt to understand systems as integrations of partially independent and interacting units--is today a dominant theme in the life sciences, cognitive science, and computer science. The concept goes back at least implicitly to the Scientific (or Copernican) Revolution, and can be found behind later theories of phrenology, physiology, and genetics; moreover, art, engineering, and mathematics rely on modular design principles. This collection broadens the scientific discussion of modularity by bringing together experts from a variety of disciplines, including artificial life, cognitive science, economics, evolutionary computation, developmental and evolutionary biology, linguistics, mathematics, morphology, paleontology, physics, theoretical chemistry, philosophy, and the arts.The contributors debate and compare the uses of modularity, discussing the different disciplinary contexts of "modular thinking" in general (including hierarchical organization, near-decomposability, quasi-independence, and recursion) or of more specialized concepts (including character complex, gene family, encapsulation, and mosaic evolution); what modules are, why and how they develop and evolve, and the implication for the research agenda in the disciplines involved; and how to bring about useful cross-disciplinary knowledge transfer on the topic. The book includes a foreword by the late Herbert A. Simon addressing the role of near-decomposability in understanding complex systems.

Evolution (Biology) --- Natural selection. --- Chaotic behavior in systems. --- Modularity (Psychology) --- Biocomplexity. --- Natural selection --- Chaotic behavior in systems --- Biocomplexity --- Biology --- Health & Biological Sciences --- Evolution --- Biological complexity --- Complexity, Biological --- Chaos in systems --- Chaos theory --- Chaotic motion in systems --- Darwinism --- Selection, Natural --- Faculty psychology --- Modules (Psychology) --- Animal evolution --- Animals --- Biological evolution --- Evolutionary biology --- Evolutionary science --- Origin of species --- Biodiversity --- Differentiable dynamical systems --- Dynamics --- Nonlinear theories --- System theory --- Genetics --- Variation (Biology) --- Biological invasions --- Heredity --- Human information processing --- Biological fitness --- Homoplasy --- Phylogeny --- BIOMEDICAL SCIENCES/Evolution --- BIOMEDICAL SCIENCES/General

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This book contains selected and revised papers of the International Symposium on Knowledge Discovery and Emergent Complexity in Bioinformatics (KDECB 2006), held at the University of Ghent, Belgium, May 10, 2006. In February 1943, the Austrian physicist Erwin Schrodi ¨ nger, one of the founding fathers of quantum mechanics, gave a series of lectures at Trinity College in Dublin titled “What Is Life? The Physical Aspect of the Living Cell and Mind. ” In these l- tures Schrodi ¨ nger stressed the fundamental differencesencountered between observing animate and inanimate matter, and advanced some, at the time, audacious hypotheses aboutthe nature andmolecularstructureof genes, some ten yearsbeforethe discoveries of Watson and Crick. Indeed, the rules of living matter, from the molecular level to the level of supraorganic ocking behavior, seem to violate the simple basic interactions found between fundamental particles as electrons and protons. It is as if the organic molecules in the cell ‘know’ that they are alive. Despite all external stochastic uct- tions and chaos, process and additive noise, this machinery has been ticking for at least 3. 8 billion years. Yet, we may safely assume that the laws that governphysicsalso steer these complex associations of synchronous and seemingly intentional dynamics in the cell.

Computational Biology --- Medical Informatics --- Data mining --- Bioinformatics --- Computational biology --- Biocomplexity --- Computational complexity --- Exploration de données (Informatique) --- Bio-informatique --- Complexité de calcul (Informatique) --- methods --- Congresses. --- Data processing --- Congrès --- Congresses --- Methods --- Publication Formats --- Information Science --- Investigative Techniques --- Biology --- Informatics --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Biological Science Disciplines --- Publication Characteristics --- Natural Science Disciplines --- Disciplines and Occupations --- Computer Science --- Engineering & Applied Sciences --- Natural Sciences --- Physical Sciences --- Discipline, Natural Science --- Disciplines, Natural Science --- Natural Science --- Natural Science Discipline --- Physical Science --- Science, Natural --- Science, Physical --- Sciences, Natural --- Sciences, Physical --- Biologic Sciences --- Biological Science --- Science, Biological --- Sciences, Biological --- Biological Sciences --- Life Sciences --- Biologic Science --- Biological Science Discipline --- Discipline, Biological Science --- Disciplines, Biological Science --- Life Science --- Science Discipline, Biological --- Science Disciplines, Biological --- Science, Biologic --- Science, Life --- Sciences, Biologic --- Sciences, Life --- Investigative Technics --- Investigative Technic --- Investigative Technique --- Technic, Investigative --- Technics, Investigative --- Technique, Investigative --- Techniques, Investigative --- Information Sciences --- Science, Information --- Sciences, Information --- Computer Science, Medical --- Health Information Technology --- Informatics, Clinical --- Informatics, Medical --- Information Science, Medical --- Clinical Informatics --- Medical Computer Science --- Medical Information Science --- Health Information Technologies --- Information Technologies, Health --- Information Technology, Health --- Medical Computer Sciences --- Medical Information Sciences --- Science, Medical Computer --- Technologies, Health Information --- Technology, Health Information --- Biological complexity --- Complexity, Biological --- Bio-Informatics --- Biology, Computational --- Computational Molecular Biology --- Molecular Biology, Computational --- Bio Informatics --- Bio-Informatic --- Bioinformatic --- Biologies, Computational Molecular --- Biology, Computational Molecular --- Computational Molecular Biologies --- Molecular Biologies, Computational --- Methodological Studies --- Methodological Study --- Procedures --- Studies, Methodological --- Study, Methodological --- Method --- Procedure --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Life sciences. --- Mathematical statistics. --- Data mining. --- Information storage and retrieval. --- Artificial intelligence. --- Bioinformatics. --- Biochemistry. --- Life Sciences. --- Biochemistry, general. --- Data Mining and Knowledge Discovery. --- Artificial Intelligence (incl. Robotics). --- Information Storage and Retrieval. --- Computational Biology/Bioinformatics. --- Probability and Statistics in Computer Science. --- Biological chemistry --- Chemical composition of organisms --- Organisms --- Physiological chemistry --- Chemistry --- Medical sciences --- Bio-informatics --- Biological informatics --- Information science --- Systems biology --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Database searching --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Biosciences --- Science --- Composition --- Statistical methods --- Information storage and retrieva. --- Computer science. --- Artificial Intelligence. --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval