Explaining the connection, if any, between simplicity and truth is among the deepest problems facing the philosophy of science, statistics, and machine learning. Say that an efficient truth finding method minimizes worst case costs en route to converging to the true answer to a theory choice problem. Let the costs considered include the number of times a false answer is selected, the number of times opinion is reversed, and the times at which the reversals occur. It is demonstrated that (1) always choosing the simplest theory compatible with experience, and (2) hanging onto it while it remains simplest, is both necessary and sufficient for efficiency.

Increasingly, epistemologists are becoming interested in social structures and their effect on epistemic enterprises, but little attention has been paid to the proper distribution of experimental results among scientists. This paper will analyze a model first suggested by two economists, which nicely captures one type of learning situation faced by scientists. The results of a computer simulation study of this model provide two interesting conclusions. First, in some contexts, a community of scientists is, as a whole, more reliable when its members are less aware of their colleagues’ experimental results. Second, there is a robust tradeoff between the reliability of a community and the speed with which it reaches a correct conclusion.

The simple question, what is empirical success? turns out to have a surprisingly complicated answer. We need to distinguish between meritorious fit and ‘fudged fit’, which is akin to the distinction between prediction and accommodation. The final proposal is that empirical success emerges in a theory dependent way from the agreement of independent measurements of theoretically postulated quantities. Implications for realism and Bayesianism are discussed.

The most recent resurgence of philosophical attention to the so-called ‘functional talk’ in the sciences can be summarized in terms of the following questions: (Q1) What kind of restrictions, and in particular, what kind of evolutionary restrictions as well as to what extent, is involved in functional ascriptions? (Q2) How can we account for the explanatory import of function-ascribing statements? This paper addresses these questions through a modified version of Cummins’ functional analysis. The modification in question is concerned with phylogenetical restrictions on causal role functions, and it stems from an analysis of some primary areas in molecular biology. I examine how evolutionary consideration affects the so-called ‘function-analytical explanatory strategy’ (Cummins [1975] 1998, 2002). Finally, I argue that the neo-functional analysis here proposed accounts for a certain convergence between the main rival theories of biological function.

Do evolutionary processes such as selection and random drift cause evolutionary change, or are they merely convenient ways of describing or summarizing it? Philosophers have lined up on both sides of this question. One recent defense (Reisman and Forber 2005) of the causal status of selection and drift appeals to a manipulability theory of causation. Yet, even if one accepts manipulability, there are still reasons to doubt that genetic drift, in particular, is genuinely causal. We will address two challenges to treating drift as causal within a manipulation framework. We will argue that both challenges ultimately fail, but that they raise interesting and subtle issues about the nature of causation and the differences between selection and drift.

In this essay I first provide an analysis of various community concepts. Second, I evaluate two of the most serious challenges to the existence of communities—gradient and paleoecological analysis respectively—arguing that, properly understood, neither threatens the existence of communities construed interactively. Finally, I apply the same interactive approach to ecosystem ecology, arguing that ecosystems may exist robustly as well.

Robert MacArthur's mathematical ecology is often regarded as ahistorical and has been criticized by historically oriented ecologists and philosophers for ignoring the importance of history. I clarify and defend his approach, especially his use of simple mathematical models to explain patterns in data and to generate predictions that stimulate empirical research. First I argue that it is misleading to call his approach ahistorical because it is not against historical explanation. Next I distinguish three kinds of criticism of his approach and argue that his approach is compatible with the first two of them. Finally, I argue that the third kind of criticism, advanced by Kim Sterelny and Paul Griffiths, is largely irrelevant to MacArthur's approach.

This paper brings needed clarity to the influential view that species are cohesive entities held together by gene flow, and then develops an empirical argument against that view: Neglected data suggest gene flow is neither necessary nor sufficient for species cohesion. Implications are discussed.

One controversy about the existence of so called evolutionary forces such as natural selection and random genetic drift concerns the sense in which such “forces” can be said to interact. In this paper I explain how natural selection and random drift can interact. In particular, I show how population-level probabilities can be derived from individual-level probabilities, and explain the sense in which natural selection and drift are embodied in these population-level probabilities. I argue that whatever causal character the individual-level probabilities have is then shared by the population-level probabilities, and that natural selection and random drift then have that same causal character. Moreover, natural selection and drift can then be viewed as two aspects of probability distributions over frequencies in populations of organisms. My characterization of population-level probabilities is largely neutral about what interpretation of probability is required, allowing my approach to support various positions on biological probabilities, including those which give biological probabilities one or another sort of causal character.

The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology. For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available. In contrast, I think that optimality models have a permanent role in evolutionary study. I base my argument for this claim on what I think it takes to best explain an event. In certain contexts, optimality and game-theoretic models best explain some central types of evolutionary phenomena.

In their paper, “Vexing Expectations,” Nover and Hájek (2004) present an allegedly paradoxical betting scenario which they call the Pasadena Game (PG). They argue that the silence of standard decision theory concerning the value of playing PG poses a serious problem. This paper provides a threefold response. First, I argue that the real problem is not that decision theory is “silent” concerning PG, but that it delivers multiple conflicting verdicts. Second, I offer a diagnosis of the problem based on the insight that standard decision theory is, rightly, sensitive to order. Third, I describe a new betting scenario—the Alternating St. Petersburg Game—which is genuinely paradoxical. Standard decision theory is silent on the value of playing this game even if restrictions are placed on the order in which the various alternative payoffs are summed.

The Variety of Evidence Thesis (VET) says that (ceteris paribus) the more diverse (or varied) of two bodies of evidence is the more confirmatory of a hypothesis H. Two recent types of Bayesian explication of VET account for the intuitive force of VET by defining variety as some function of the probabilities of the propositions which collectively constitute a body of evidence. I show that these two accounts of VET are not tracking a meaningful property of bodies of evidence, but rather are tracking artifacts of how those bodies of evidence are described. According to each account, whether a body of evidence is more varied than another depends on how the bodies are split into parts. Furthermore, for each type of account there exists a way to redescribe the total evidence such that any two totalities are equally varied.

We consider to what extent the fundamental question of spacetime singularities is relevant for the philosophical debate about the nature of spacetime. After reviewing some basic aspects of the spacetime singularities within general relativity, we argue that the well known difficulty to localize them in a meaningful way may challenge the received metaphysical view of spacetime as a set of points possessing some intrinsic properties together with some spatiotemporal relations. Considering the algebraic formulation of general relativity, we argue that the spacetime singularities highlight the philosophically misleading dependence on the standard geometric representation of spacetime.

It is claimed that unacceptable constraints on initial data are imposed by certain responses to paradoxes that threaten time travel, closed timelike curves (CTCs) and other backwards causation hypotheses. In this paper I argue against the following claims: to say “contradictions are impossible so something must prevent the paradox” commits in general to constraints on initial data, that for fixed point dynamics so-called grey state solutions explain why contradictions do not arise, and the latter have been proved to avoid constraints on initial data.

The Copenhagen interpretation, which informs the textbook presentation of quantum mechanics, depends fundamentally on the notion of ontological wave-particle duality and a viewpoint called “complementarity.” In this paper, Bohr's own interpretation is traced in detail and is shown to be fundamentally different from and even opposed to the Copenhagen interpretation in virtually all its particulars. In particular, Bohr's interpretation avoids the ad hoc postulate of wave function ‘collapse’ that is central to the Copenhagen interpretation. The strengths and weakness of both interpretations are summarized.

I examine recent arguments based on functionalism that claim to show that Bohm's theory fails to solve the measurement problem, or if it does so, it is only because it reduces to a form of the many-worlds theory. While these arguments reveal some interesting features of Bohm's theory, I contend that they do not undermine the distinctive Bohmian solution to the measurement problem.

A paradigmatic shift in the foundations of quantum mechanics is recorded, from interpreting to reconstructing quantum theory. Examples of reconstruction are analyzed, and conceptual foundations of the information-theoretic reconstruction developed. A concept of intentionally incomplete reconstruction is introduced to mark the novel content of research in the foundation of quantum theory.

This paper introduces a new equilibrium concept for normal form games called dependency equilibrium; it is defined, exemplified, and compared with Nash and correlated equilibria in Sections 2–4. Its philosophical motive is to rationalize cooperation in the one shot prisoners’ dilemma. A brief discussion of its meaningfulness in Section 5 concludes the paper.

How do rational agents coordinate in a single-stage, noncooperative game? Common knowledge of the payoff matrix and of each player's utility maximization among his strategies does not suffice. This paper argues that utility maximization among intentions and then acts generates coordination yielding a payoff-dominant Nash equilibrium.