Igor Douven

There is an ongoing controversy in philosophy about the connection between explanation and inference. According to Bayesians, explanatory considerations should be given weight in determining which inferences to make, if at all, only insofar as doing so is compatible with Strict Conditionalization. Explanationists, on the other hand, hold that explanatory considerations can be relevant to the question of how much confidence to invest in our hypotheses in ways which violate Strict Conditionalization. The controversy has focused on normative issues. This paper investigates experimentally the descriptive question of whether judgments of the explanatory goodness of hypotheses do play a role when people revise their degrees of belief in those hypotheses upon the receipt of new evidence. We present the results of three experiments that together strongly support the predictive superiority of the explanationist position

So far, color-naming studies have relied on a rather limited set of color stimuli. Most importantly, stimuli have been largely limited to highly saturated colors. Because of this, little is known about how people categorize less saturated colors and, more generally, about the structure of color categories as they extend across all dimensions of color space. This article presents the results from a large Internet-based color-naming study that involved color stimuli ranging across all available chroma levels in Munsell space. These results help answer such questions as how English speakers name a more complex color set, whether English speakers use so-called basic color terms (BCTs) more frequently for more saturated colors, how they use non-BCTs in comparison with BCTs, whether non-BCTs are highly consensual in less saturated parts of the solid, how deep inside color space basic color categories extend, or how they behave on the chroma dimension.

In van Fraassen's The Scientific Image we are told that the scientific anti‐realist need not appeal to some special semantics for scientific language. He can allegedly hold – just like his direct opponents typically do – that truth‐conditional semantics is appropriate both for claims about the observable and claims about the unobservable. However, I shall point out that this kind of semantics goes badly with the anti‐realist's epistemic attitude vis‐his the unobservable. In this paper an alternative semantics shall be outlined that is perfectly compatible with the rest of the anti‐realist's position. Although this alternative semantics will be seen to fly in the face of the established doctrine in the field, I shall argue that there is currently no good reason not to adopt it. It will further be pointed out that this semantics has something to be recommended from a realist perspective as well.

The Principle of the Benefit of Doubt dictates that, whenever reasonably possible, we interpret earlier-day scientists as referring to entities posited by current science. Putnam has presented the principle as supplementary to his Causal Theory of Reference in order to make this theory generally applicable to theoretical terms. The present paper argues that the principle is of doubtful standing. In particular, it will be argued that the principle lacks a justification and, indeed, is unjustifiable as it stands.

This article addresses two questions related to colour categorization, to wit, the question what a colour category is, and the question how we identify colour categories. We reject both the relativist and universalist answers to these questions. Instead, we suggest that colour categories can be identified with the help of the criterion of psychological saliency, which can be operationalized by means of consistency and consensus measures. We further argue that colour categories can be defined as well-structured entities that optimally partition colour space. We provide some empirical support for this claim by presenting experimental results, which indicate that internal structure is a better predictor of colour categories than perceptual saliency

Many philosophers deny that happiness can be equated with pleasurable experiences. Nozick introduced an experience machine thought experiment to support the idea that happiness requires pleasurable experiences that are “in contact with reality.” In this thought experiment, people can choose to plug into a machine that induces exclusively pleasurable experiences. We test Nozick’s hypothesis that people will reject this offer. We also contrast Nozick’s experience machine scenario with scenarios that are less artificial, and offer options which are less invasive or disruptive than being connected to a machine, specifically scenarios in which people are offered an experience pill or a pill that improves overall functioning.

Conceptual spaces have become an increasingly popular modeling tool in cognitive psychology. The core idea of the conceptual spaces approach is that concepts can be represented as regions in similarity spaces. While it is generally acknowledged that not every region in such a space represents a natural concept, it is still an open question what distinguishes those regions that represent natural concepts from those that do not. The central claim of this paper is that natural concepts are represented by the cells of an optimally designed similarity space.

Unger (1974/2000) presents an argument for skepticism that significantly differs from the more traditional arguments for skepticism. The argument is based on two premises, to wit, that knowledge would entitle the knower to absolute certainty, and that an attitude of absolute certainty is always inadmissible from an epistemic viewpoint. The present paper scrutinizes the arguments that Unger provides in support of these premises and shows that none of them is tenable. It thus concludes that Unger's argument for skepticism fails to threaten the possibility of knowledge.

We present a model for studying communities of epistemically interacting agents who update their belief states by averaging the belief states of other agents in the community. The agents in our model have a rich belief state, involving multiple independent issues which are interrelated in such a way that they form a theory of the world. Our main goal is to calculate the probability for an agent to end up in an inconsistent belief state due to updating. To that end, an analytical expression is given and evaluated numerically, both exactly and using statistical sampling. It is shown that, under the assumptions of our model, an agent always has a probability of less than 2% of ending up in an inconsistent belief state. Moreover, this probability can be made arbitrarily small by increasing the number of independent issues the agents have to judge or by increasing the group size. A real-world situation to which this model applies is a group of experts participating in a Delphi-study

The gift of life argument, the claim that suicide is immoral because our lives are not ours to dispose of as we are their guardians or stewards, is a persistent theme in debates about the morality of suicide, assisted-suicide, and euthanasia. I argue that this argument suffers from a fatal internal incoherence. The gift can either be interpreted literally or analogically. If it is interpreted literally there are serious problems in understanding who receives the gift. If it is understood analogically the question arises whether the gift is understood to be a finite or everlasting existence. If it is finite then it is hard to see how one can be punished for bringing that existence to an end for one will not be around to be punished. If the existence is infinite it is impossible to see how one can be punished for ending one’s life because one cannot end it. However, there is still ethical mileage to be gained from the description of life as a gift and in the concluding section I indicate one way in which this is so

Regier, Kay, and Khetarpal report the results of computer simulations that cluster color stimuli on the basis of their coordinates in CIELAB space, one of two commonly used perceptual color spaces. Regier and coauthors find partitions of those stimuli that are strikingly similar to the way actual color lexicons partition color space. They do not argue for the custom-made clustering method used in their simulations, nor for the assumption of CIELAB space. The present paper aims to answer the question to what extent their computational results depend on these assumptions. It does this by applying a great variety of known clustering methods to Regier et al.’s stimuli, and by assuming not only CIELAB space but also CIELUV space, the other main color space.