Modularity is one of the most important concepts used to articulate a theory of cognitive architecture. Over the last 30 years, the debate in many areas of the cognitive sciences and in philosophy of psychology about what modules are, and to what extent our cognitive architecture is modular, has made little progress. After providing a diagnosis of this lack of progress, this article suggests a remedy. It argues that the theoretical framework of network science can be brought to bear on the traditional modularity debate, facilitating our progress in articulating a good theory of the human cognitive architecture.

In this essay, I argue that uneliminated idealizations pose a serious problem for scientific realism. I consider one method for “de-idealizing” models—robustness analysis. However, I argue that unless idealizations are eliminated from an idealized theory and robustness analysis need not do that, scientists are not justified in believing that the theory is true. I consider one example of modeling from the biological sciences that exemplifies the problem.

The explanatory significance of equilibrium depends on the underlying dynamics. A number of questions of stability and robustness are relevant. Here I investigate these questions with respect to some simple evolutionary models from my book, Evolution of the Social Contract. These models use the replicator dynamics. In each of these models I identify the equilibria and characterize their local dynamic stability properties. In two of the models, I show that one equilibrium is globally asymptotically stable. I then show that the foregoing results are robust over a large class of adaptive dynamics that might be considered as alternatives to the replicator dynamics. I investigate the structural stability properties of the three models. The question of the structural stability of a model of bargaining with correlated encounters raised by D'Arms, Batterman, and Górny (1998) is answered in the affirmative. The other two models are not structurally stable. Modification of a structurally unstable signaling system to allow for correlated encounters results in a structurally stable model.

In considering the possibility that the fundamental particles of matter might violate Leibniz's Principle, one is confronted with logical proofs that the Principle is a Theorem of Logic. This paper shows that the proof of that theorem is not universal enough to encompass entities that might not be unique, and also strongly suggests that photons, for example, do violate Leibniz's Principle. It also shows that the existence of non-individuals would imply the breakdown of Quine's criterion of ontological commitment.

This paper examines the relationship between modern theories of microeconomics and macroeconomics and, more generally, it evaluates the prospects of theoretically reducing macroeconomics to microeconomics. Many economists have shown strong interest in providing “microfoundations” for macroeconomics and much of their work is germane to the issue of theoretical reduction. Especially relevant is the work that has been done on what is called The Problem of Aggregation. On some accounts, The Problem of Aggregation just is the problem of reducing macroeconomics to microeconomics. I show how to separate these problems and then try to determine to what extent particular kinds of solutions to The Problem of Aggregation succeed in reducing macroeconomics to microeconomics as well. I argue that reduction is not possible by this means given the current state of microeconomics. I also describe how reduction may be possible by means of (dis)aggregation if microeconomics is supplemented in a certain way with the results of experimental research on individual economic agents.

This paper places formal learning theory in a broader philosophical context and provides a glimpse of what the philosophy of induction looks like from a learning-theoretic point of view. Formal learning theory is compared with other standard approaches to the philosophy of induction. Thereafter, we present some results and examples indicating its unique character and philosophical interest, with special attention to its unified perspective on inductive uncertainty and uncomputability.

In this paper I attempt to show that adaptational sentences (i.e. sentences containing the terms “adaptive”, “adapted”, etc.) in evolutionary biology are best interpreted as equivalent to sentences about Darwinian or genetical selection. Thus, the use of adaptational languages does not introduce final purposes or other nonempirical notions into biology. I also try to demonstrate that adaptational sentences and functional sentences are not equivalent in an evolutionary context so that an analysis of function does not dispense with the need for an analysis of adaptation. Finally, it is argued that, although some adaptational sentences might be construed as teleological explanations, given an empirical content, they do not serve as explanations. Rather, they express the outcome of selection, regarded in one way, and regarded in another, they express data for which a theory of evolution must account.

One construal of convergent realism is that for each clear question, scientific inquiry eventually answers it. In this paper we adapt the techniques of formal learning theory to determine in a precise manner the circumstances under which this ideal is achievable. In particular, we define two criteria of convergence to the truth on the basis of evidence. The first, which we call EA convergence, demands that the theorist converge to the complete truth “all at once”. The second, which we call AE convergence, demands only that for every sentence in the theorist's language, there is a time at which the theorist settles the status of the sentence. The relative difficulties of these criteria are compared for effective and ineffective agents. We then examine in detail how the enrichment of an agent's hypothesis language makes the task of converging to the truth more difficult. In particular, we parametrize first-order languages by predicate and function symbol arity, presence or absence of identity, and quantifier prefix complexity. For nearly each choice of values of these parameters, we determine the senses in which effective and ineffective agents can converge to the complete truth on an arbitrary structure for the language. Finally, we sketch directions in which our learning theoretic setting can be generalized or made more realistic.

I begin by distinguishing two notions of model, the notion of a truth-making structure and the notion of a mathematical model (in one specific sense). I then argue that although the models of the semantic view have often been taken to be both truth-making structures and mathematical models, this is in part due to a failure to distinguish between two ways of truth-making; in fact, the talk of truth-making is best excised from the view altogether. The result is a version of the semantic view which is better supported by the direct evidence offered for it, better equipped to achieve its avowed aims, and, I think, closer to the intentions of the original proponents of the view in many ways, despite some of their own declarations to the contrary.

Biological systems exhibit complexity at all levels of organization. It has recently been argued by Michael Behe that at the biochemical level a type of complexity exists—irreducible complexity—that cannot possibly have arisen as the result of natural, evolutionary processes and must instead be the product of (supernatural) intelligent design. Recent work on self-organizing chemical reactions calls into question Behe's analysis of the origins of biochemical complexity. His central interpretative metaphor for biochemical complexity, that of the well-designed mousetrap that ceases to function if critical parts are absent, is undermined by the observation that typical biochemical systems exhibit considerable redundancy and overlap of function. Real biochemical systems, we argue, manifest redundant complexity—a characteristic result of evolutionary processes.

Hempel's paradox of the ravens arises from the inconsistency of three prima facie plausible principles of confirmation. This paper uses Camapian inductive logic to (a) identify which of the principles is false, (b) give insight into why this principle is false, and (c) identify a true principle that is sufficiently similar to the false one that failure to distinguish the two might explain why the false principle is prima facie plausible. This solution to the paradox is compared with a variety of other responses and is shown to differ from all of them.

How, if at all, does the internal structure of human phenomenological color space map onto the internal structure of objective reflectance-profile space, in such a fashion as to provide a useful and accurate representation of that objective feature space? A prominent argument (due to Hardin, among others) proposes to eliminate colors as real, objective properties of objects, on grounds that nothing in the external world (and especially not surface-reflectance-profiles) answers to the well-known and quite determinate internal structure of human phenomenological color space. The present paper proposes a novel way to construe the objective space of possible reflectance profiles so that (1) its internal structure becomes evident, and (2) that structure's homomorphism with the internal structure of human phenomenological color space becomes obvious. The path is thus reopened to salvage the objective reality of colors, in the same way that we preserved the objective reality of such features as temperature, pitch, and sourness—by identifying them with some objective feature recognized in modern physical theory.

This paper argues against the deductive reconstruction of scientific prediction, that is, against the view that in prediction the predicted event follows deductively from the laws and initial conditions that are the basis of the prediction. The major argument of the paper is intended to show that the deductive reconstruction is an inaccurate reconstruction of actual scientific procedure. Our reason for maintaining that it is inaccurate is that if the deductive reconstruction were an accurate reconstruction, then scientific prediction would be impossible.

The propagation of causal influences through space-time seems to play a fundamental role in scientific explanation. Taking as a point of departure a basic distinction between causal interactions (which are localized in space-time) and causal processes (which may extend through vast regions of space-time), this paper attempts an analysis of the concept of causal propagation on the basis of the ability of causal processes to transmit “marks.” The analysis rests upon the “at-at” theory of motion which has figured prominently in the resolution of Zeno's arrow paradox. It is argued that this explication does justice to the concept of the ability of causal processes to transmit causal influence without invoking anti-Humean “powers” or “necessary connections.”

This paper examines the so-called “gauge argument” sometimes used by physicists to motivate the introduction of gauge fields, here facilitated by an informal exposition of the fiber bundle formalism. The discussion suggests some preliminary ways of understanding the connection between gauge fields and interactions.

The problem of idealization in empirical sciences is very rarely taken up in works concerned with the methodology of those sciences. It seems to be common knowledge that in advanced natural sciences references are made to concepts such as “perfectly rigid body,” “material point,” “perfect gas,” etc., but it remains a fact that the most important methodological concepts, concepts which have determined the present-day form of the philosophy of science, have been advanced without regard to the peculiarities of the procedure mentioned above. And yet a moment's consideration suffices to raise doubts as to Carnap's physicalism and/or Popper's falsificationism if we just realize the trivial and commonly known truth that empirical sciences resort to idealizationism. For how are we to imagine a reduction of idealizational concepts to observation terms? And how are we to imagine that theorems which include idealizational concepts imply observation statements which refute, or at least are at variance with, those theorems? But it is a fact that such doubts have neither been raised by the authors of the conceptions mentioned above, nor have they been raised (as far as the present writer is informed) against them.

Current theories of the division of cognitive labor are confined to the “context of justification,” assuming exogenous theories. But new theories are made from the same labor that is used for developing existing theories, and if none of this labor is ever allocated to create new alternatives, then scientific progress is impossible. A unified model is proposed in which theories are no longer given but a function of the division of labor in the model itself. The interactions of individuals balancing the exploitation of existing theories and the exploration of new theories results in a robust cyclical pattern.

The main thrust of the paper involves a theoretical and philosophical analysis of the claim made in September 1999 that atomic orbitals have been directly imaged for the first time. After a brief account of the recent claims the paper reviews the development of the orbit and later orbital concepts and analyzes the theoretical status of atomic orbitals. The conclusion is that contrary to these claims, atomic orbitals have not in fact been observed. The non-referring nature of modern atomic orbitals is discussed in the context of Laudan's writings on realism, the success of theories, and whether or not scientific terms refer. I conclude that the failure to observe orbitals is a good prima facie case for divorcing the success of theories from the question of whether their central terms refer. The added relevance of this case is that it concerns a current and highly successful theory. Finally, the relevance of this ‘floating model’ to contemporary discussions on scientific models is briefly considered.

Putnam and Finkelstein have proposed the abandonment of distributivity in the logic of quantum theory. This change results from defining the connectives, not truth-functionally, but in terms of a certain empirical ordering of propositions. Putnam has argued that the use of this ordering (“implication”) to govern proofs resolves certain paradoxes. But his resolutions are faulty; and in any case, the paradoxes may be resolved with no changes in logic. There is therefore no reason to regard the partially ordered set of propositions as a logic—i.e. as embodying a criterion for soundness of proofs. Its role in quantum theory ought to be understood in an entirely different way.