‘Bayesian epistemology’ became an epistemological movement in the 20th century, though its two main features can be traced back to the eponymous Reverend Thomas Bayes (c. 1701-61). Those two features are: (1) the introduction of a formal apparatus for inductive logic; (2) the introduction of a pragmatic self-defeat test (as illustrated by Dutch Book Arguments) for epistemic rationality as a way of extending the justification of the laws of deductive logic to include a justification for the laws of inductive logic. (...) The formal apparatus itself has two main elements: the use of the laws of probability as coherence constraints on rational degrees of belief (or degrees of confidence) and the introduction of a rule of probabilistic inference, a rule or principle of conditionalization. (shrink)

Epistemology is the study of knowledge and justified belief. Belief is thus central to epistemology. It comes in a qualitative form, as when Sophia believes that Vienna is the capital of Austria, and a quantitative form, as when Sophia's degree of belief that Vienna is the capital of Austria is at least twice her degree of belief that tomorrow it will be sunny in Vienna. Formal epistemology, as opposed to mainstream epistemology (Hendricks 2006), is epistemology done in a formal way, (...) that is, by employing tools from logic and mathematics. The goal of this entry is to give the reader an overview of the formal tools available to epistemologists for the representation of belief. A particular focus will be the relation between formal representations of qualitative belief and formal representations of quantitative degrees of belief. (shrink)

Determining the precise nature of the connection between preference, choice, and welfare has arguably been the central project in the field of welfare economics, which aims to offer a proper guide for economists in the making of policy decisions that affect people’s welfare. The two leading approaches here historically – the revealed preference and latent preference approaches – seem equally incapable of so guiding economists. I argue that the deadlock here is due to welfare economists’ failure to recognize a crucial (...) distinction between two senses of “preference.” I analyze and defend these senses of “preference,” and argue that each shares a close connection with just one of choice and welfare. This analysis reveals how economists should conceive of both the connections between “preference,” choice, and welfare, and the proper roles of these concepts in welfare economics. I conclude by showing this analysis to best explain the plausibility of two leading alternative approaches from Hausman and Sugden. (shrink)

Decision theory and folk psychology both purport to represent the same phenomena: our belief-like and desire- and preference-like states. They also purport to do the same work with these representations: explain and predict our actions. But they do so with different sets of concepts. There's much at stake in whether one of these two sets of concepts can be accounted for with the other. Without such an account, we'd have two competing representations and systems of prediction and explanation, a dubious (...) dualism. Folk psychology structures our daily lives and has proven fruitful in the study of mind and ethics, while decision theory is pervasive in various disciplines, including the quantitative social sciences, especially economics, and philosophy. My interest is in accounting for folk psychology with decision theory -- in particular, for believe and wanting, which decision theory omits. Many have attempted this task for belief. (The Lockean Thesis says that there is such an account.) I take up the parallel task for wanting, which has received far less attention. I propose necessary and sufficient conditions, stated in terms of decision theory, for when you're truly said to want; I give an analogue of the Lockean Thesis for wanting. My account is an alternative to orthodox accounts that link wanting to preference (e.g. Stalnaker (1984), Lewis (1986)), which I argue are false. I argue further that want ascriptions are context-sensitive. My account explains this context-sensitivity, makes sense of conflicting desires, and accommodates phenomena that motivate traditional theses on which 'want' has multiple senses (e.g. all-things-considered vs. pro tanto). (shrink)

So-called “traditional epistemology” and “Bayesian epistemology” share a word, but it may often seem that the enterprises hardly share a subject matter. They differ in their central concepts. They differ in their main concerns. They differ in their main theoretical moves. And they often differ in their methodology. However, in the last decade or so, there have been a number of attempts to build bridges between the two epistemologies. Indeed, many would say that there is just one branch of philosophy (...) here—epistemology. There is a common subject matter after all. In this paper, we begin by playing the role of a “bad cop,” emphasizing many apparent points of disconnection, and even conflict, between the approaches to epistemology. We then switch role, playing a “good cop” who insists that the approaches are engaged in common projects after all. We look at various ways in which the gaps between them have been bridged, and we consider the prospects for bridging them further. We conclude that this is an exciting time for epistemology, as the two traditions can learn, and have started learning, from each other. (shrink)

The Rachels–Temkin spectrum arguments against the transitivity of better than involve good or bad experiences, lives, or outcomes that vary along multiple dimensions—e.g., duration and intensity of pleasure or pain. This paper presents variations on these arguments involving combinations of good and bad experiences, which have even more radical implications than the violation of transitivity. These variations force opponents of transitivity to conclude that something good is worse than something that isn’t good, on pain of rejecting the good altogether. That (...) is impossible, so we must reject the spectrum arguments. (shrink)

Computational philosophy is the use of mechanized computational techniques to instantiate, extend, and amplify philosophical research. Computational philosophy is not philosophy of computers or computational techniques; it is rather philosophy using computers and computational techniques. The idea is simply to apply advances in computer technology and techniques to advance discovery, exploration and argument within any philosophical area. -/- After touching on historical precursors, this article discusses contemporary computational philosophy across a variety of fields: epistemology, metaphysics, philosophy of science, ethics and (...) social philosophy, philosophy of language and philosophy of mind, often with examples of operating software. Far short of any attempt at an exhaustive treatment, the intention is to introduce the spirit of each application by using some representative examples. (shrink)

This monograph introduces a meta-framework for conducting interdisciplinary research in the science of emotion, as well as a framework for a particular kind of theory of emotion. It can also be understood as a “cross-over” book that introduces neophytes to some of the current discourse and major challenges for an interdisciplinary approach to the science of emotion, especially from a philosophical perspective. It also engages experts from across the disciplines who are interested in conducting an interdisciplinary approach to research and (...) theorizing in the science of emotion, and introduces to them some of the contemporary debates in the philosophy of emotion. It does so by providing a taxonomy of theories of emotion which allows one to understand the contemporary interdisciplinary discourse in the science of emotion as a debate between four fundamental types of theories of emotion—realism, instrumentalism, eliminative-realism, and eliminativism—and which can be found or potentially found across the disciplines, and by arguing for foundational principles which can unify, without consilience, these four kinds of approaches as perspectives about the same object of inquiry. It also covers a wide range of concerns, including the problem of skepticism in the science of emotion, the problem of the underdetermination of a theory by the evidence, the question of the place of ordinary intuitions and ordinary language for a science of emotion, the mind-body problem, the hard problem of consciousness, the meta-hard problem of consciousness, the problem of intentionality, questions about the rationality of emotions and whether emotions can be a vehicle for knowledge, and the debate between cognitive and noncognitive theories in the philosophy of emotion. (shrink)

According to success semantics, a belief’s content is that which guarantees the success of the actions that the belief, in combination with the relevant desires, would cause. One worry with the view is that it seems to apply only to full beliefs and fares poorly in dealing with partial beliefs. For example, if Ida’s partial belief that p is of strength 0.5, she may act in a way that would fulfill her desires if p were in fact false—assuming that she (...) desires money, she may well accept a bet that pays her $500 if not-p and costs her nothing otherwise. In response to the worry, defenders of success semantics hold that the content of a partial belief is simply that which guarantees the success of the actions it would cause were it a full belief. But, as I’ll argue in this paper, such a response is unsatisfactory. (shrink)