Representation (systemics)

About: Representation (systemics) is a research topic. Over the lifetime, 33821 publications have been published within this topic receiving 475461 citations.

The hippocampus as a predictive map

Abstract: The authors show how predictive representations are useful for maximizing future reward, particularly in spatial domains. They develop a predictive-map model of hippocampal place cells and entorhinal grid cells that captures a wide variety of effects from human and rodent literature. A cognitive map has long been the dominant metaphor for hippocampal function, embracing the idea that place cells encode a geometric representation of space. However, evidence for predictive coding, reward sensitivity and policy dependence in place cells suggests that the representation is not purely spatial. We approach this puzzle from a reinforcement learning perspective: what kind of spatial representation is most useful for maximizing future reward? We show that the answer takes the form of a predictive representation. This representation captures many aspects of place cell responses that fall outside the traditional view of a cognitive map. Furthermore, we argue that entorhinal grid cells encode a low-dimensionality basis set for the predictive representation, useful for suppressing noise in predictions and extracting multiscale structure for hierarchical planning.

Computer graphic display visualization system and method

Abstract: An improved human user computer interface system, providing a graphic representation of a hierarchy populated with naturally classified objects, having included therein at least one associated object having a distinct classification. Preferably, a collaborative filter is employed to define the appropriate associated object. The associated object preferably comprises a sponsored object, generating a subsidy or revenue.

The Promise and Perils of Alternative Forms of Data Representation

Abstract: This article addresses the potential strengths and weaknesses of alternative forms of data representation. As educational researchers become increasingly interested in the relationship between form of representation and form of understanding, new representational forms are being used to convey to "readers" what has been learned. These explorations are rooted in an expanding conception of the nature of knowledge and the relationship between what one knows and how it is represented. While new forms of representation have their potential virtues, they also have their limitations. The uses and limitations of these new methods are addressed in what follows.

Digital Pictures: Representation and Compression

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