Peter Smith

A wide range of ecological and evolutionary models predict variety in phenotype or behavior when a population is at equilibrium. This heterogeneity can be realized in different ways. For example, it can be realized through a complex population of individuals exhibiting different simple behaviors, or through a simple population of individuals exhibiting complex, varying behaviors. In some theoretical frameworks these different realizations are treated as equivalent, but natural selection distinguishes between these two alternatives in subtle ways. By investigating an increasingly complex series of models, from a simple fluctuating selection model up to a finite population hawk/dove game, we explore the selective pressures which discriminate between pure strategists, mixed at the population level, and individual mixed strategists. Our analysis reveals some important limitations to the ESS framework often employed to investigate the evolution of complex behavior.

It is well known that informational theories of representation have trouble accounting for error. Informational semantics is a family of theories attempting a naturalistic, unashamedly reductive explanation of the semantic and intentional properties of thought and language. Most simply, the informational approach explains truth-conditional content in terms of causal, nomic, or simply regular correlation between a representation and a state of affairs. The central work is Dretske, and the theory was largely developed at the University of Wisconsin by Fred Dretske, Dennis Stampe, and Berent Enc. Recently, informational semantics has roamed far beyond its Wisconsin home, and built a sizeable collection of followers. Converts include Jerry Fodor, Robert Stalnaker and, less faithfully, Paul and Patricia Churchland and Hartry Field. But for some years informational semantics has been hounded by a problem with error – the classic presentation is Fodor – and no other problem has hounded the theory so persistently.

Gary Ebbs: Quine's Naturalistic Explication of Carnap's Logic of Science: If one studies Quine's epistemology without appreciating its deep connections to Carnap's logic of science, one can easily get the impression that unlike Carnap, Quine aims to preserve and clarify the traditional empiricist idea that our best theories of nature are justified by, or based on, our sensory evidence, and are for that reason likely to be true. Quine writes, for instance, that [The] human subject is accorded a certain experimentally controlled input—certain patterns of irradiation in assorted frequencies, for instance—and in the fullness of time the subject delivers as output a description of the three‐dimensional external world and its history. The relation between the meager input and the torrential output is a relation that we are prompted to study for somewhat the same reasons that always prompted epistemology; namely, in order to see how evidence relates to theory, and in what ways one's theory of nature transcends any available evidence. Commenting on this and similar passages in Quine, Barry Stroud writes: … the question Quine poses in terms of the “underdetermination” of the “torrential output” by the “meager input” makes essential use of a notion of epistemic priority. It is because the “information” we get at “input” does not uniquely determine the truth of what we assert as “output” that we must explain how we get from the one to the other. I argue that despite its superficial plausibility, this interpretation of Quine is mistaken: following Carnap, yet also radically transforming his views, Quine takes our best current theory as our ultimate arbiter of truth. The goal of Quine's naturalistic account of the relationship between theory and evidence is not to show that our best theories of nature are justified by our sensory evidence, but to show that we can describe science from within science itself in a way that mirrors and thereby clarifies his doctrinal principle that we can only judge truth from the standpoint of our best current theory.

An interpretation is given of John Dewey's views about “realism” in metaphysics, and of how these views relate to contemporary debates. Dewey rejected standard formulations of realism as a general metaphysical position, and interpreters have often been taken him to be sympathetic to some form of verificationism or constructivism. I argue that these interpretations are mistaken, as Dewey's unease with standard formulations of realism comes from his philosophical emphasis on intelligent control of events, by means of ordinary action. Because of his views about relations, Dewey's views in this area do risk collapsing into an overly holistic position. I discuss how these problems might be avoided, and consider also how Dewey's views about naturalism and realism might usefully inform ongoing work

Many vertebrate animals approximate, to various degrees, the “split‐brain” condition that results from surgery done in humans to treat severe epilepsy, with very limited connection between the left and right sides of the upper parts of the brain. The split‐brain condition has been the topic of extensive philosophical discussion, because it appears, in some circumstances, to give rise to two minds within one body. Is the same true of these animals? This article attempts to make progress on two difficult topics—animal experience, and the consequences of the human split‐brain condition—by considering both at once.

This book presents a collection of linked essays written by one of the leading philosophers of biology, Kim Sterelny, on the topic of biological evolution. The first half of the book explores most of the main theoretical controversies about evolution and selection. Sterelny argues that genes are not the only replicators: non-genetic inheritance is also extremely important, and is no mere epiphenomenon of gene selection. The second half of the book applies some of these ideas in considering cognitive evolution. Concentrating on the mental capacities of simpler animals rather than those of humans, Sterelny argues for a general distinction between detection and representation, and that the evolution of belief, like that of representation, can be decoupled from the evolution of preference. These essays, some never before published, form a coherent whole that defends not just an overall conception of evolution, but also a distinctive take on cognitive evolution.

Our understanding of communication and its evolution has advanced significantly through the study of simple models involving interacting senders and receivers of signals. Many theorists have thought that the resources of mathematical information theory are all that are needed to capture the meaning or content that is being communicated in these systems. However, the way theorists routinely talk about the models implicitly draws on a conception of content that is richer than bare informational content, especially in contexts where false content is important. This article shows that this concept can be made precise by defining a notion of functional content that captures the degree to which different states of the world are involved in stabilizing senders’ and receivers’ use of a signal at equilibrium. A series of case studies is used to contrast functional content with informational content, and to illustrate the explanatory role and limitations of this definition of functional content. _1_ Introduction _2_ Modelling Framework _3_ Two Kinds of Content _3.1_ Informational content _3.2_ Functional content _4_ Cases _4.1_ Case 1: Simplest case _4.2_ Case 2: Partial pooling _4.3_ Case 3: Bottleneck _4.4_ Case 4: Partial common interest _4.5_ Case 5: Deception _4.6_ Case 6: A further problem arising from divergent interests _5_ Discussion Appendix

Modeling work by Brian Skyrms and others in recent years has transformed the theoretical role of David Lewis's 1969 model of signaling. The latter can now be understood as a minimal model of communication in all its forms. In this article, we explain how the Lewis model has been generalized, and consider how it and its variants contribute to ongoing debates in several areas. Specifically, we consider connections between the models and four topics: The role of common interest in communication, signaling within the organism, meaning, and the evolution of human communication and language.

Group-structured populations, of the kind prominent in discussions of multilevel selection, are contrasted with ‘neighbor-structured’ populations. I argue that it is a necessary condition on multilevel description of a selection process that there should be a nonarbitrary division of the population into equivalence classes (or an approximation to this situation). The discussion is focused via comparisons between two famous problem cases involving group structure (altruism and heterozygote advantage) and two neighbor-structured cases that resemble them. Conclusions are also drawn about the role of correlated interaction in the evolution of altruism. 1 Introduction 2 Two Kinds of Population Structure 3 Objections and Replies 4 Particles on a Line 5 Conclusion Appendix: Neighborhoods and Selection CiteULike    Connotea    Del.icio.us    What's this?