Scientific discovery is often regarded as romantic and creative - and hence unanalyzable - whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human thought (...) processes used to discover scientific laws. The programs - BACON, DALTON, GLAUBER, and STAHL - are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along. "Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science. Pat Langley is an Associate Professor in the Department of Information and Computer Science at the University of California, Irvine.Herbert Simon is a Professor in the Departments of Psychology, Computer Science, and Philosophy at Carnegie-Mellon University. Gary L. Bradshaw is an Assistant Professor in the Department of Psychology and Institute of Cognitive Science at the University of Colorado, Boulder. Jan M. Zytkow is an Associate Professor in the Computer Science Department at Wichita State University. (shrink)

The fundamental tenet of contemporary sociobiology, namely the assumption of a single process of evolution involving the selection of genes, is critically examined. An alternative multiple-level, multiple-process model of evolution is presented which posits that the primary process that operates via selection upon the genes cannot account for certain kinds of biological phenomena, especially complex, learned, social behaviours. The primary process has evolved subsidiary evolutionary levels and processes that act to bridge the gap between genes and these complex behaviours. The (...) subsidiary levels are development, individual animal learning, and socioculture itself. It is argued that individual learning is pivotal to the derivation and biological analysis of culture. The differences between cultural and noncultural societies are stressed. It is concluded that such a multiple-level model of evolution can form the basis for reconciling opposing sides in the sociobiology debate. (shrink)

Classifying is a fundamental operation in the acquisition of knowledge. Taxonomic theory can help students of cognition, evolutionary psychology, ethology, anatomy, and sociobiology to avoid serious mistakes, both practical and theoretical. More positively, it helps in generating hypotheses useful to a wide range of disciplines. Composite wholes, such as species and societies, are “individuals” in the logical sense, and should not be treated as if they were classes. A group of analogous features is a natural kind, but a group of (...) homologous features is not. Imposing hypotheses justified only on the basis of nominalist, realist, phenomenalist, or conceptualist metaphysics upon the neurophysiology of organisms or upon the causes of behavior exemplifies the “psychologist's fallacy” of William James. Levels should be distinguished from their members and from classes of levels, and the ontological status of entities ranked at levels should be made clear. It is important not to confuse such categories as substance and process with one another. Several genetical terms, such as “gene” and chromosome,” are even more equivocal than has been realized. Discussions about units of selection, behavior, and thinking suffer from the ambiguity of a “unit of” an entity. An important source of misunderstanding about natural selection is the habit of treating it as an “agent”: in an important sense, natural selection does not “act” at all. (shrink)

The Postlude, written for this edition, looks back at the predictions made more than twenty-five years ago and speculates about what the coming decades may hold ...

The Nature of Selection is a straightforward, self-contained introduction to philosophical and biological problems in evolutionary theory. It presents a powerful analysis of the evolutionary concepts of natural selection, fitness, and adaptation and clarifies controversial issues concerning altruism, group selection, and the idea that organisms are survival machines built for the good of the genes that inhabit them. "Sober's is the answering philosophical voice, the voice of a first-rate philosopher and a knowledgeable student of contemporary evolutionary theory. His book merits (...) broad attention among both communities. It should also inspire others to continue the conversation."-Philip Kitcher, Nature "Elliott Sober has made extraordinarily important contributions to our understanding of biological problems in evolutionary biology and causality. The Nature of Selection is a major contribution to understanding epistemological problems in evolutionary theory. I predict that it will have a long lasting place in the literature."-Richard C. Lewontin. (shrink)

"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)

The ultimate source of explanation in biology is the principle of natural selection. Natural selection means differential reproduction of genes and gene combinations. It is a mechanistic process which accounts for the existence in living organisms of end-directed structures and processes. It is argued that teleological explanations in biology are not only acceptable but indeed indispensable. There are at least three categories of biological phenomena where teleological explanations are appropriate.

Most biologists and some cognitive scientists have independently reached the conclusion that there is no such thing as learning in the traditional “instructive‘ sense. This is, admittedly, a somewhat extreme thesis, but I defend it herein the light of data and theories jointly extracted from biology, especially from evolutionary theory and immunology, and from modern generative grammar. I also point out that the general demise of learning is uncontroversial in the biological sciences, while a similar consensus has not yet been (...) reached in psychology and in linguistics at large. Since many arguments presently offered in defense of learning and in defense of “general intelligence‘ are often based on a distorted picture of human biological evolution, I devote some sections of this paper to a critique of “adaptationism,‘ providing also a sketch of a better evolutionary theory. Moreover, since certain standard arguments presented today as “knock-down‘ in psychology, in linguistics and in artificial intelligence are a perfect replica of those once voiced by biologists in favor of instruction and against selection, I capitalize on these errors of the past to draw some lessons for the present and for the future. (shrink)

Introduction: How hard is the "hard core" of a scientific program? / Massimo Piattelli-Palmarini -- pt. 1. The debate: 1. Opening the debate: The psychogenesis of knowledge and its epistemological significance / Jean Piaget -- On cognitive structures and their development: a reply to Piaget / Noam Chomsky -- 2. About the fixed nucleus and its innateness: Introductory remarks / Jean Piaget -- Cognitive strategies in problem solving / Guy Cellerier -- Some clarifications on innatism and constructivism / Guy Cellerier (...) -- 3. Artificial intelligence and general development mechanisms: The role of artificial intelligence in psychology / Seymour Papert -- 4. Initial states and steady states: The linguistic approach / Noam Chomsky -- 5. Cognitive schemes and their possible relations to language acquisition: Language and knowledge in a constructivist framework / Bäé́ Thom -- Appendix C: Localist hypothesis and theory of catastrophes: note on the debate / Jean Petitot. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

Let psychologism be the doctrine that whether behavior is intelligent behavior depends on the character of the internal information processing that produces it. More specifically, I mean psychologism to involve the doctrine that two systems could have actual and potential behavior _typical_ of familiar intelligent beings, that the two systems could be exactly alike in their actual and potential behavior, and in their behavioral dispositions and capacities and counterfactual behavioral properties (i.e., what behaviors, behavioral dispositions, and behavioral capacities they would (...) have exhibited had their stimuli differed)--the two systems could be alike in all these ways, yet there could be a difference in the information processing that mediates their stimuli and responses that determines that one is not at all intelligent while the other is fully intelligent. (shrink)

Formulation of a general model of evolution is presented which is based upon the recognition of the ?biosocial? entity, that is the biosphere and human society, as a component?system. It can be demonstrated that the interactions of the components (moleculas, cells, organisms, ecosystems in the biological realms and people, artifacts and ideas in the societies) have replicative organization. We suggest an explanation for the spontaneous emergence of replicative function and organization, a process called autogenesis. During autogenesis, hierarchical levels of replicative (...) organization emerge and compartmentalization and convergence of replicative information occurs. Questions of the origin and evolution of life are discussed. The replicative paradigm can also be applied to the processes of cultural evolution, in which complex replicative networks of people, ideas, and man?made artifacts show all stages and phenomena of autogenesis. Finally, the present state of evolution of the whole global biosocial system is discussed. (shrink)

Evolution in the sense of the new paradigm embraces not only the emergence of biological species but also development in the cosmos and in history. It means ?grand synthesis,? or general theory of evolution. Its roots lie in the search for meaning that inspired systematic thought since its inception: its historical antecedents go back to the Ionian natural philosophers. Today the evolutionary paradigm frames invariant scientific concepts that appear in specific transformations in the physical, the biological, and the human and (...) social disciplines. The new general laws of evolution exhibit overarching orders that encompass nature as well as humanity and respond to a perennial search for unity and meaning in experience. (shrink)

A lecture before the Harvard Natural History Society; published in the Atlantic Monthly; and later republished in James (1897)The Will to Believe and Other Essays in Popular Philosophy.

The discovery of the concrete basis for genes, and especially the clarification of mechanisms regulating gene expressions (in particular those that bear on the stepwise processing of hereditary information from the sequences of DNA nucleotides to the proteins) was to give flesh to the concept of a genetic program, for these regulations introduce relationships of order between the various elements of information contained in the genes. These order relations are then revealed during the time-dependent expression of the genetic program. They (...) can lead, in the case of a given program, to a plethora of particular outcomes, because the number of possible combinations rapidly becomes enormous. Since the discoveries of Jacob and Monod, it is clear that the genes specifying the regulatory functions will be responsible for phenotypic variability, especially for the apparently ideal adaptation of a living organism to its environment, and more generally for all the genotype-bound manifestations as they unfold in time. -/- Thus we are led to consider three particular characteristics that allow for the representation of living beings: a program, which summarizes the hereditary constraints and is, in fact, the abstract notion underlying the definition of all individuals in a given class (species); an initial state of the system that represents the context in which the program must express itself at the time of the individual's birth; and a particular outcome of each program, which coincides with individual development. The set of all outcomes constitutes the genetic envelope and allows the essential characteristics of the program to be obtained by induction. Theoretically, a structured set equivalent to the aforementioned one could be reconstructed by providing the program, the initial state, and the totality of the events of the external environment, producing any interaction whatever with the individual. -/- As a consequence, the observation of a phenotype does not tell in any straightforward way, what is the direct consequence of the expression of a particular gene, or of a specific feature of the environment. A phenocopy is a particular example of a phenotype that is the result of a gene expression mimicking a particular gene-directed phenotype, without however corresponding to a pparticular mutation of a known gene. (shrink)

Discusses mental processes, the role of humans in nature, experience, and the connection between myth, religion, and science.

Traditionally a scientific theory is viewed as based on universal laws of nature that serve as axioms for logical deduction. In analyzing the logical structure of evolutionary biology, Elisabeth Lloyd argues that the semantic account is more appropriate and powerful. This book will be of interest to biologists and philosophers alike.