Learn More
This article proposes a new model of human concept learning that provides a rational analysis of learning feature-based concepts. This model is built upon Bayesian inference for a grammatically structured hypothesis space-a concept language of logical rules. This article compares the model predictions to human generalization judgments in several well-known(More)
An important element of learning from examples is the extraction of patterns and regularities from data. This paper investigates the structure of patterns in data defined over discrete features, i.e. features with two or more qualitatively distinct values. Any such pattern can be algebraically decomposed into a spectrum of component patterns, each of which(More)
We demonstrate that a single moving object can create the subjective impression that it is alive, based solely on its pattern of movement. Our displays differ from conventional biological motion displays (which normally involve multiple moving points, usually integrated to suggest a human form) in that they contain only a single rigid object moving across a(More)
This paper investigates perceptual grouping from a logical point of view, defining a grouping interpretation as a particular kind of logical expression, and then developing an explicit inference theory in terms of such expressions. First, a regularity-based interpretation language is presented, in which an observed configuration is characterized in terms of(More)
The notion that visual attention can operate over visual objects in addition to spatial locations has recently received much empirical support, but there has been relatively little empirical consideration of what can count as an 'object' in the first place. We have investigated this question in the context of the multiple object tracking paradigm, in which(More)
This paper presents a logic-based approach to grouping and perceptual organization, called Minimal Model theory, and presents efficient methods for computing interpretations in this framework. Grouping interpretations are first defined as logical structures, built out of atomic qualitative scene descriptors (" regularities ") that are derived from(More)
The process by which the human visual system parses an image into contours, surfaces, and objects--perceptual grouping--has proven difficult to capture in a rigorous and general theory. A natural candidate for such a theory is Bayesian probability theory, which provides optimal interpretations of data under conditions of uncertainty. But the fit of Bayesian(More)