In this paper I defend an etiological theory of biological functions (according to which the proper function of a trait is the effect for which it was selected by natural selection) against three objections which have been influential. I argue, contrary to Millikan, that it is wrong to base our defense of the theory on a rejection of conceptual analysis, for conceptual analysis does have an important role in philosophy of science. I also argue that biology requires a normative notion (...) of a "proper function", and that a normative notion is not ahistorical. (shrink)

Murray Gell-Mann has proposed the concept of effective complexity as a measure of information content. The effective complexity of a string of digits is defined as the algorithmic complexity of the regular component of the string. This paper argues that the effective complexity of a given string is not uniquely determined. The effective complexity of a string admitting a physical interpretation, such as an empirical data set, depends on the cognitive and practical interests of investigators. The effective complexity of a (...) string as a purely formal construct, lacking a physical interpretation, is either close to zero, or equal to the string's algorithmic complexity, or arbitrary, depending on the auxiliary criterion chosen to pick out the regular component of the string. Because of this flaw, the concept of effective complexity is unsuitable as a measure of information content. (shrink)

The etiological approach to ‘proper functions’ in biology can be strengthened by relating it to Robert Cummins' general treatment of function ascription. The proper functions of a biological trait are the functions it is assigned in a Cummins-style functional explanation of the fitness of ancestors. These functions figure in selective explanations of the trait. It is also argued that some recent etiological theories include inaccurate accounts of selective explanation in biology. Finally, a generalization of the notion of selective explanation allows (...) an analysis of the proper functions of human artifacts. (shrink)

The prelims comprise: Introduction Semantic Information The Mathematical Theory of Communication Some Philosophical Approaches to Semantic Information Conclusion Acknowledgments Some Web Resources.

This ongoing bestseller, now in its third edition, is considered the standard reference on Kolmogorov complexity, a modern theory of information that is concerned with information in individual objects. -/- New key features and topics in the 3rd edition: -/- * New results on randomness -/- * Kolmogorov's structure function, model selection, and MDL -/- * Incompressibility method: counting unlabeled graphs, Shellsort, communication complexity -/- * Derandomization -/- * Kolmogorov complexity versus Shannon information, rate distortion, lossy compression, denoising -/- * (...) Theoretical results on information distance -/- * The similarity metric with applications to genomics, phylogeny, clustering, classification, semantic meaning, question-answer systems -/- * Quantum Kolmogorov complexity -/- Written by two experts in the field, this book is ideal for advanced undergraduate students, graduate students, and researchers in all fields of science. It is self-contained: it contains the basic requirements from mathematics, probability theory, statistics, information theory, and computer science. Included are history, theory, new developments, a wide range of applications, numerous (new) problem sets, comments, source references, and hints to solutions of problems. This is the only comprehensive treatment of the central ideas of Kolmogorov complexity and their applications. (shrink)

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske‐Grice approach: meaningful and well‐formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth‐values do not supervene on (...) semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo‐information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo‐information. As a consequence, SDI is revised to include a necessary truth‐condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition. (shrink)

The papers gathered in this book were published over a period of more than twenty years in widely scattered journals. They led to the discovery of randomness in arithmetic which was presented in the recently published monograph on?Algorithmic Information Theory? by the author. There the strongest possible version of G”del's incompleteness theorem, using an information-theoretic approach based on the size of computer programs, was discussed. The present book is intended as a companion volume to the monograph and it will serve (...) as a stimulus for work on complexity, randomness and unpredictability, in physics and biology as well as in metamathematics. (shrink)

What makes a living system a living system? What kind of biological phenomenon is the phenomenon of cognition? These two questions have been frequently considered, but, in this volume, the authors consider them as concrete biological questions. Their analysis is bold and provocative, for the authors have constructed a systematic theoretical biology which attempts to define living systems not as objects of observation and description, nor even as interacting systems, but as self-contained unities whose only reference is to themselves. The (...) consequence of their investigations and of their living systems as self-making, self-referring autonomous unities, is that they discovered that the two questions have a common answer: living systems are cognitive systems, and living as a process is a process of cognition. The result of their investigations is a completely new perspective of biological (human) phenomena. During the investigations, it was found that a complete linguistic description pertaining to the ‘organization of the living’ was lacking and, in fact, was hampering the reporting of results. Hence, the authors have coined the word ‘autopoiesis’ to replace the expression ‘circular organization’. Autopoiesis conveys, by itself, the central feature of the organization of the living, which is autonomy. (shrink)

Stuart Kauffman here presents a brilliant new paradigm for evolutionary biology, one that extends the basic concepts of Darwinian evolution to accommodate recent findings and perspectives from the fields of biology, physics, chemistry and mathematics. The book drives to the heart of the exciting debate on the origins of life and maintenance of order in complex biological systems. It focuses on the concept of self-organization: the spontaneous emergence of order widely observed throughout nature. Kauffman here argues that self-organization plays an (...) important role in the emergence of life itself and may play as fundamental a role in shaping life's subsequent evolution as does the Darwinian process of natural selection. Yet until now no systematic effort has been made to incorporate the concept of self-organization into evolutionary theory. The construction requirements which permit complex systems to adapt remain poorly understood, as is the extent to which selection itself can yield systems able to adapt more successfully. This book explores these themes. It shows how complex systems, contrary to expectations, can spontaneously exhibit stunning degrees of order, and how this order, in turn, is essential for understanding the emergence and development of life on Earth. Topics include the new biotechnology of applied molecular evolution, with its important implications for developing new drugs and vaccines; the balance between order and chaos observed in many naturally occurring systems; new insights concerning the predictive power of statistical mechanics in biology; and other major issues. Indeed, the approaches investigated here may prove to be the new center around which biologicalscience itself will evolve. The work is written for all those interested in the cutting edge of research in the life sciences. (shrink)

The mathematical theory of communication.

Many mechanisms, functions and structures of life have been unraveled. However, the fundamental driving force that propelled chemical evolution and led to life has remained obscure. The second law of thermodynamics, written as an equation of motion, reveals that elemental abiotic matter evolves from the equilibrium via chemical reactions that couple to external energy towards complex biotic non-equilibrium systems. Each time a new mechanism of energy transduction emerges, e.g., by random variation in syntheses, evolution prompts by punctuation and settles to (...) a stasis when the accessed free energy has been consumed. The evolutionary course towards an increasingly larger energy transduction system accumulates a diversity of energy transduction mechanisms, i.e. species. The rate of entropy increase is identified as the fitness criterion among the diverse mechanisms, which places the theory of evolution by natural selection on the fundamental thermodynamic principle with no demarcation line between inanimate and animate. (shrink)