John Symons

An asymmetry between the demands at the computational and algorithmic levels of description furnishes the illusion that the abstract profile at the computational level can be multiply realized, and that something is actually being shared at the algorithmic one. A disembodied rendering of the situation lays the stress upon the different ways in which an algorithm can be implemented. However, from an embodied approach, things look rather different. The relevant pairing, I shall argue, is not between implementation and algorithm, but rather between algorithm and computation. The autonomy of psychology is a result of the failure to appreciate this point.

Rather than taking the ontological fundamentality of an ideal microphysics as a starting point, this article sketches an approach to the problem of levels that swaps assumptions about ontology for assumptions about inquiry. These assumptions can be implemented formally via computational modeling techniques that will be described below. It is argued that these models offer a way to save some of our prominent commonsense intuitions concerning levels. This strategy offers a way of exploring the individuation of higher level properties in a systematic and formally constrained manner. †To contact the author, please write to: Department of Philosophy, Worrell Hall 306, 500 University Avenue, University of Texas, El Paso, TX 79968; e‐mail: [email protected].

Skeptics argue that the acquisition of knowledge is impossible given the standing possibility of error. We present the limiting convergence strategy for responding to skepticism and discuss the relationship between conceivable error and an agent’s knowledge in the limit. We argue that the skeptic must demonstrate that agents are operating with a bad method or are in an epistemically cursed world. Such demonstration involves a significant step beyond conceivability and commits the skeptic to potentially convergent inquiry.

Giandomenico Sica’s volume is a collection of eleven papers on category theory by philosophers, mathematicians, and mathematical physicists. In addition to papers of direct interest to philosophers of mathematics, the volume contains some introductory expositions of category theory along with a valuable discussion of the relationship between category theory and physics by Bob Coecke. While there are several technically difficult papers, the volume as a whole is reasonably accessible to those with some familiarity with the basics of category theory. The importance of the volume lies in the possibility that it will encourage broader interest in category theory among philosophers.

Functionalism in the philosophy of mind rests on the claim that mental states are multiply realizable; mental states can be realized by or instantiated in a variety of distinct physical structures. To see them as multiply realizable we take mental states as causal roles rather than particular physical structures. As such, functionalism can be contrasted with metaphysical accounts which treat mental states as instances of a mental substance. Instead of puzzling over the relationship between mental and physical kinds, functionalists understand our talk of minds as a way of describing the functions of bodies. The attraction of a functionalist position is obvious. It seems to solve the traditional problem of mind-body dualism, while simultaneously reconciling the apparent irreducibility of psychological discourse with a broadly physicalistic or materialistic ontology.

Computational modeling plays an increasingly important explanatory role in cases where we investigate systems or problems that exceed our native epistemic capacities. One clear case where technological enhancement is indispensable involves the study of complex systems.1 However, even in contexts where the number of parameters and interactions that define a problem is small, simple systems sometimes exhibit non-linear features which computational models can illustrate and track. In recent decades, computational models have been proposed as a way to assist us in understanding emergent phenomena.

This volume gathers together essays from some of Hintikka’s colleagues and former students exploring his influence on their work and pursuing some of the insights that we have found in his work. This book includes a comprehensive overview of Hintikka’s philosophy by Dan Kolak and John Symons and an annotated bibliography of Hintikka’s work. Table of Contents: Foreword; Daniel Kolak and John Symons. Hintikka on Epistemological Axiomatizations; Vincent F. Hendricks. Hintikka on the Problem with the Problem of Transworld Identity; Troy Catterson. What is Epistemic Discourse About? Radu J. Bogdan. Interrogative Logic and the Economic Theory of Information; Raymond Dacey. A Metalogical Critique of Wittgensteinian ‘Phenomenology’; William Boos. Theoretical Commensurability By Correspondence Relations: When Empirical Success Implies Theoretical Reference; Gerhard Schurz. What is Abduction?: An Assessment of Jaakko Hintikka's Conception; James H. Fetzer. The dialogic of just being different: Hintikka's new approach to the notion of episteme and its impact on 'second generation' dialogics; Shahid Rahman. Probabilistic Features in Logic Games; Johan F. A. K. van Benthem. On Some Logical Properties of ‘Is True’; Jan Wolenski. The Results are in: The Scope and Import of Hintikka's Philosophy; Daniel Kolak and John Symons. Annotated Bibliography of Jaakko Hintikka. Index.

This paper argues that the difference between contemporary software intensive scientific practice and more traditional non-software intensive varieties results from the characteristically high conditionality of software. We explain why the path complexity of programs with high conditionality imposes limits on standard error correction techniques and why this matters. While it is possible, in general, to characterize the error distribution in inquiry that does not involve high conditionality, we cannot characterize the error distribution in inquiry that depends on software. Software intensive science presents distinctive error and uncertainty modalities that pose new challenges for the epistemology of science

Horgan’s perceptive discussion of Freudian psychology, Prozac and evolutionary biology cannot mitigate the problems that seriously weaken his book (Horgan, 1999). While he certainly manages to deflate some of the more outrageous hype surrounding the scientific and often not-so-scientific study of the mind, his criticism of the brain and behavioral sciences contains a number of flaws, some of which I will address below. My response focuses on his discussion of neuroscience. As we shall see, the three mysteries that Horgan believes cripple neuroscience are certainly not as serious as he insists.

In this paper, we argue for the centrality of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions. By irreversibility, we mean the fact that computational models can generally arrive at the same state via many possible sequences of previous states. Thus, while in the natural world, it is generally assumed that physical states have a unique history, representations of those states in a computational model will usually be compatible with more than one possible history in the model. We describe some of the challenges involved in prediction and retrodiction in computational models while arguing that prediction is an essential feature of non-arbitrary decision making. Furthermore, we contend that the non-predictive virtues of computational models are dependent to a significant degree on the predictive success of the models in question.

SPECIAL INTRODUCTORY PRICE! Daniel Dennett has been one of the central voices in the philosophy of mind for at least the past forty years. Unlike most philosophers of his generation, Dennett’s work has resonated far and wide. It has powerfully influenced the development of cognitive science, robotics, developmental psychology, and artificial intelligence. Indeed, his work has led to many new lines of inquiry. For example, he has developed a theory of consciousness which provides an approach to naturalizing mind which circumvents many of the most significant philosophical arguments against the possibility of a scientific explanation of consciousness. The daunting quantity of literature available on Dennett makes it difficult to discriminate the useful from the tendentious, superficial, and otiose. Moreover, because no comparable philosopher has had a profound impact across such a wide range of disciplines and on intellectual culture in general, responses to Dennett’s philosophy are dispersed across a broad range of scientific, philosophical, and cultural domains. That is why this new title in the highly regarded Routledge series, Critical Assessments of Leading Philosophers, is so urgently needed. Edited by John Symons, this new Routledge Major Work is a four-volume collection of the best scholarship on Dennett; the collected materials have been carefully selected from a wide range of academic journals, edited collections, research monographs, and other sources. The tightly focused organization of this collection allows users quickly and easily to access both established and cutting-edge assessments of Dennett’s work. The set is also made for irresistible browsing. With comprehensive introductions to each volume, providing essential background information and relating the various works to each other, Daniel Dennett is destined to be an indispensable resource for research and study

The analytic tradition is sometimes criticized as being narrowly focused on language, logic or conceptual analysis to the detriment of deeper investigations into ontological, metaphysical or moral questions.1 More specifically, analytic philosophy has been associated with a positivist attitude which favored replacing the philosophy’s traditional focus on fundamental questions with an obsequiously deferential relationship to mathematics and the natural sciences. While this line of criticism obscures the historical reality and contemporary diversity of the analytic tradition, it is certainly true that analytic philosophers have generated severe criticisms of traditional metaphysics.

Epistemic logic begins with the recognition that our everyday talk about knowing and believing has some systematic features that we can track and re‡ect upon. Epistemic logicians have studied and extended these glints of systematic structure in fascinating and important ways since the early 1960s. However, for one reason or another, mainstream epistemologists have shown little interest. It is striking to contrast the marginal role of epistemic logic in contemporary epistemology with the centrality of modal logic for metaphysicians. This article is intended to help in correcting this oversight by presenting some important developments in epistemic logic and suggesting ways to understand their applicability to traditional epistemological problems. Obviously, by itself, tweaking the formal apparatus of epistemic logic does not solve traditional epistemological problems. Epistemic logic can help us to navigate through problems in a systematic fashion by unpacking the logic of the problematic concepts, it can also lead us to recognize problems that we had not anticipated. This is basically analogous to the role that modal logic has played in contemporary metaphysics.