Drawing on lay epistemology theory, the authors assessed a terror management analysis of the psychological function of structuring social information. Seven studies tested variations of the hypothesis that simple, benign interpretations of social information function, in part, to manage death-related anxiety. In Studies 1-4, mortality salience (MS) exaggerated primacy effects and reliance on re...

In this paper we explore the relationship between “preference elicitation”, a learning-style problem that arises in combinatorial auctions, and the problem of learning via queries studied in computational learning theory. Preference elicitation is the process of asking questions about the preferences of bidders so as to best divide some set of goods. As a learning problem, it can be thought of ...

In this paper, we show that personalized levels can be automatically generated for platform games. We build on previous work, where models were derived that predicted player experience based on features of level design and on playing styles. These models are constructed using preference learning, based on questionnaires administered to players after playing different levels. The contributions o...

We propose a versatile framework for combining knowledge bases in modular systems with preferences. In our formalism, each module (knowledge base) can be specified in a different language. We define the notion of a preference-based modular system that includes a formalization of metapreferences. We prove that our formalism is robust in the sense that the operations for combining modules preserv...

Rational accounts of decision-making are incompatible with the prevalence and success of ubiquitous marketing strategies. In this paper, we demonstrate, using computational experiments, how an ideal Bayesian observer model of preference learning is compatible with the manipulation of purchasing decisions via a number of well-known marketing techniques. The ability of this model to predict the e...

In this paper, we present a novel approach which incorporates the web-derived selectional preferences to improve statistical dependency parsing. Conventional selectional preference learning methods have usually focused on word-to-class relations, e.g., a verb selects as its subject a given nominal class. This paper extends previous work to wordto-word selectional preferences by using webscale d...

People routinely draw inferences about others’ preferences by observing their decisions. We study these inferences by characterizing a space of simple observed decisions. Previous work on attribution theory has identified several factors that predict whether a given decision provides strong evidence for an underlying preference. We identify one additional factor and show that a simple probabili...