" Biosemantics " was the title of a paper on mental representation originally printed in The Journal of Philosophy in 1989. It contained a much abbreviated version of the work on mental representation in Language Thought and Other Biological Categories. There I had presented a naturalist theory of intentional signs generally, including linguistic representations, graphs, charts and diagrams, road sign symbols, animal communications, the "chemical signals" that regulate the function of glands, and so forth. But the term " biosemantics " (...) has usually been applied only to the theory of mental representation. Let me first characterize a more general class of theories called "teleological theories of mental content" of which biosemantics is an example. Then I will discuss the details that distinguish biosemantics from other naturalistic teleological theories. (shrink)

A brief personal history is given about how information theory can be applied to binding sites of genetic control molecules on nucleic acids. The primary example used is ribosome binding sites in Escherichia coli. Once the sites are aligned, the information needed to describe the sites can be computed using Claude Shannon’s method. This is displayed by a computer graphic called a sequence logo. The logo represents an average binding site, and the mathematics easily allows one to determine the components (...) of this average. That is, given a set of binding sites, the information for individual binding sites can also be computed. One can go further and predict the information of sites that are not in the original data set. Information theory also allows one to model the flexibility of ribosome binding sites, and this led us to a simple model for ribosome translational initiation in which the molecular components fit together only when the ribosome is at a good ribosome binding site. Since information theory is general, the same mathematics applies to human splice junctions, where we can predict the effect of sequence changes that cause human genetic diseases and cancer. The second example given is the Pribnow “box,” which, when viewed by the information theory method, reveals a mechanism for initiation of both transcription and DNA replication. Replication, transcription, splicing, and translation into protein represent the central dogma, so these examples show how molecular information theory is contributing to our knowledge of basic biology. (shrink)

A brief personal history is given about how information theory can be applied to binding sites of genetic control molecules on nucleic acids. The primary example used is ribosome binding sites in Escherichia coli. Once the sites are aligned, the information needed to describe the sites can be computed using Claude Shannon’s method. This is displayed by a computer graphic called a sequence logo. The logo represents an average binding site, and the mathematics easily allows one to determine the components (...) of this average. That is, given a set of binding sites, the information for individual binding sites can also be computed. One can go further and predict the information of sites that are not in the original data set. Information theory also allows one to model the flexibility of ribosome binding sites, and this led us to a simple model for ribosome translational initiation in which the molecular components fit together only when the ribosome is at a good ribosome binding site. Since information theory is general, the same mathematics applies to human splice junctions, where we can predict the effect of sequence changes that cause human genetic diseases and cancer. The second example given is the Pribnow “box,” which, when viewed by the information theory method, reveals a mechanism for initiation of both transcription and DNA replication. Replication, transcription, splicing, and translation into protein represent the central dogma, so these examples show how molecular information theory is contributing to our knowledge of basic biology. (shrink)

In 1958, Francis Crick distinguished the flow of information from the flow of matter and the flow of energy in the mechanism of protein synthesis. Crick’s claims about information flow and coding in molecular biology are viewed from the perspective of a new characterization of mechanisms and from the perspective of information as holding a key to distinguishing work in molecular biology from that of biochemistry in the 1950s–1970s . Flow of matter from beginning to end does not occur in (...) the protein synthesis mechanism; flow of information does. The flow of information and coding in molecular biological mechanisms are distinguished, on the one hand, from formal information theory, and, on the other, from information as used in cognitive neuroscience, where information and representation are often coupled. (shrink)

Information about the environment is captured in human biological systems on a variety of interacting levels – in distributions of genes, linguistic particulars, concepts, methods, theories, preferences, and overt behaviors. I investigate some of the basic principles which govern such a hierarchy by constructing a comparatively simple three-level selection model of bee foraging preferences and behaviors. The information-theoretic notion of ''''mutual information'''' is employed as a measure of efficiency in tracking a changing environment, and its appropriateness in epistemological applications is (...) discussed at some length. In particular, information accumulated in mid-level preference distributions exhibits suggestive properties for the purposes of naturalistic epistemology. It also appears that the novelty of scientific objects and representations and the rapidity of scientific change relative to genetic change need present no obstacle to the use of such models in explanations of scientific progress and the reliability of scientific judgement. (shrink)

This book presents an attempt to develop a theory of knowledge and a philosophy of mind using ideas derived from the mathematical theory of communication developed by Claude Shannon. Information is seen as an objective commodity defined by the dependency relations between distinct events. Knowledge is then analyzed as information caused belief. Perception is the delivery of information in analog form for conceptual utilization by cognitive mechanisms. The final chapters attempt to develop a theory of meaning by viewing meaning as (...) a certain kind of information-carrying role. (shrink)

In this lucid portrayal of human behavior, Fred Dretske provides an original account of the way reasons function in the causal explanation of behavior.

"By combining recent advances in the physical sciences with some of the novel ideas, techniques, and data of modern biology, this book attempts to achieve a new and different kind of evolutionary synthesis. I found it to be challenging, fascinating, infuriating, and provocative, but certainly not dull."--James H, Brown, University of New Mexico "This book is unquestionably mandatory reading not only for every living biologist but for generations of biologists to come."--Jack P. Hailman, Animal Behaviour , review of the first (...) edition "An important contribution to modern evolutionary thinking. It fortifies the place of Evolutionary Theory among the other well-established natural laws."--R.Gessink, TAXON. (shrink)

In this provocative book, Fred Dretske argues that to achieve an understanding of the mind it is not enough to understand the biological machinery by means of...

The mathematical theory of communication.

Scientific knowledge grows at a phenomenal pace--but few books have had as lasting an impact or played as important a role in our modern world as The Mathematical Theory of Communication, published originally as a paper on communication theory more than fifty years ago. Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored (...) to issue this commemorative reprinting of a classic. (shrink)

I Physics of Information Information, Physics, Quantum: The Search for Links John Archibald Wheeler Information from Quantum Measurements Benjamin Schumacher Local Accessibility of Quantum States William K. Wootters The Entropy of Black Holes V. F. Mukhanov Some Simple Consequences of the Loss of Information in a Spacetime with a Horizon Shin Takagi Why is the Physical World so Comprehensible? P. C. W. Davies II Laws of Physics and Laws of Computation Algorithmic Information Content, Church-Turing Thesis, Physical Entropy, and Maxwell’s Demon (...) W. E. Zurek Entropy and Information: How Much Information is Needed to Assign a Probability? Carlton M. Caves Complexity of Models J. Rissanen Laws and Boundary Conditions C. H. Woo How to Define Complexity in Physics, and Why Charles H. Bennett III Complexity and Evolution Requirements for Evolvability in Complex Systems: Orderly Dynamics and Frozen Components Stuart A. Kauffman Valuable Information Seth Lloyd Non-Equilibrium Polymers, Entropy, and Algorithmic Information Dilip K. Kondepudi The Dynamics of Complex Computational Systems Tad Hogg Computation at the Onset of Chaos James P. Crutchfield and Karl Young IV Physics of Computation Parallel Quantum Computation Norman Margolus Information Processing at the Molecular Level: Possible Realizations and Physical Constraints W. G. Teich and G. Mahler How Cheap Can Mechanics’ First Principles Be? Tommaso Toffoli Intermittent Fluctuations and Complexity Xiao-Jing Wang Information Processing in Visual Perception A. Zee V Probability, Entropy, and Quantum Thermodynamic Constraints on Quantum Axioms Asker Peres Entropy and Quantum Mechanics M. Hossein Páriovi Einstein Completion of Quantum Mechanics Made Falsifiable O. E. Rossler Quantum Mechanics and Algorithmic Complexity J. W. Barrett Probability in Quantum Theory E. T. Jaynes Quantum Measurements and Entropy H. D. Zeh VI Quantum Theory and Measurement Quantum Mechanics in the Light of Quantum Cosmology Murray Gell-Mann and James B. Hartle Information Dissipation in Quantum Cosmology and the Emergence of Classical Spacetime Jonathan J. Halliwell The Quantum Mechanics of Self-Measurement David Z. Albert The Quantum-Classical Correspondence in Light of Classi- cal Bell’s and Quantum Tsirelson’s Inequalities X. A. Khalfin Some Progress in Measurement Theory: The Logical Inter- pretation of Quantum Mechanics Roland Omnes. (shrink)

Preface by Daniel C. Dennett Beginning with a general theory of function applied to body organs, behaviors, customs, and both inner and outer representations, ...

This book explains the relationship between intelligence and environmental complexity, and in so doing links philosophy of mind to more general issues about the relations between organisms and environments, and to the general pattern of 'externalist' explanations. The author provides a biological approach to the investigation of mind and cognition in nature. In particular he explores the idea that the function of cognition is to enable agents to deal with environmental complexity. The history of the idea in the work of (...) Dewey and Spencer is considered, as is the impact of recent evolutionary theory on our understanding of the place of mind in nature. (shrink)

Evolutionary theory offers the possibility of building an epistemology that requires neither a theory of truth nor a definition of knowledge, thus bypassing some of the more notable difficulties with standard approaches to epistemology. Following a critique of one of the most popular approaches to thinking about cultural evolution I argue for a frequentist approach to evolutionary epistemology, and that cultural transmission should be understood as coordinated phenotypic variability within groups of closely related organisms. I construct a formal system which (...) allows the analysis of the evolution of networks of multiple interacting populations. Of particular epistemological interest is the relationship between genetic evolution and the evolution of cultural entities. The information-theoretic notion of "mutual information" is employed to quantify the transfer of information from the environment as it determines genetic fitnesses into the distribution of acquired traits Two simple models are constructed and analyzed. A two-level model of the navigation of a colony of bacteria demonstrates how selection on inherited traits affects the acquisition of information on the level of transient behavioral traits. A three-level model of bumblebee foraging shows how information about the environment is caught up in distributions of acquired foraging preferences--a bee-analog of human cognitive states. The Appendix contains an analytic proof of information gain under selection. (shrink)