From the Publisher:
Probabilistic Reasoning in Intelligent Systems is a complete andaccessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertaintyand offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognitionin short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information.
Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Many teaching practices implicitly assume that conceptual knowledge can be abstracted from the situations in which it is learned and used. This article argues that this assumption inevitably limits the effectiveness of such practices. Drawing on recent research into cognition as it is manifest in everyday activity, the authors argue that knowledge is situated, being in part a product of the activity, context, and culture in which it is developed and used. They discuss how this view of knowledge affects our understanding of learning, and they note that conventional schooling too often ignores the influence of school culture on what is learned in school. As an alternative to conventional practices, they propose cognitive apprenticeship (Collins, Brown, & Newman, in press), which honors the situated nature of knowledge. They examine two examples of mathematics instruction that exhibit certain key features of this approach to teaching.

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Situated Cognition and the Culture of Learning

Bartlett viewed thinking as a high level skill exhibiting ballistic properties that he called its “point of no return”. This paper explores one aspect of cognition through the use of a simple model...

/pdf/orienting-of-attention-2bi7r8jak3.pdf

Orienting of attention

Publisher Summary
This chapter outlines the two basic routes to persuasion. One route is based on the thoughtful consideration of arguments central to the issue, whereas the other is based on the affective associations or simple inferences tied to peripheral cues in the persuasion context. This chapter discusses a wide variety of variables that proved instrumental in affecting the elaboration likelihood, and thus the route to persuasion. One of the basic postulates of the Elaboration Likelihood Model—that variables may affect persuasion by increasing or decreasing scrutiny of message arguments—has been highly useful in accounting for the effects of a seemingly diverse list of variables. The reviewers of the attitude change literature have been disappointed with the many conflicting effects observed, even for ostensibly simple variables. The Elaboration Likelihood Model (ELM) attempts to place these many conflicting results and theories under one conceptual umbrella by specifying the major processes underlying persuasion and indicating the way many of the traditionally studied variables and theories relate to these basic processes. The ELM may prove useful in providing a guiding set of postulates from which to interpret previous work and in suggesting new hypotheses to be explored in future research.

/pdf/the-elaboration-likelihood-model-of-persuasion-3y2y5dyvfe.pdf

The elaboration likelihood model of persuasion

PROBLEM TO BE SOLVED: To solve the problem, wherein it is impossible for an electronic content information provider to provide commercially secure and effective method, for a configurable general-purpose electronic commercial transaction/distribution control system. SOLUTION: In this system, having at least one protected processing environment for safely controlling at least one portion of decoding of digital information, a secure content distribution method comprises a process for encapsulating digital information in one or more digital containers; a process for encrypting at least a portion of digital information; a process for associating at least partially secure control information for managing interactions with encrypted digital information and/or digital container; a process for delivering one or more digital containers to a digital information user; and a process for using a protected processing environment, for safely controlling at least a portion of the decoding of the digital information. COPYRIGHT: (C)2006,JPO&NCIPI

https://apps.dtic.mil/dtic/tr/fulltext/u2/a423264.pdf

Systems and Methods for Secure Transaction Management and Electronic Rights Protection

On data-limited and resource-limited processes

The art of metaobject protocol

Although individual use of computers is fairly widespread, in meetings we tend to leave them behind. At Xerox PARC, an experimental meeting room called the Colab has been created to study computer support of collaborative problem solving in face-to-face meetings. The long-term goal is to understand how to build computer tools to make meetings more effective.

Beyond the chalkboard: computer support for collaboration and problem solving in meetings

The use of narrative and other prose forms as a tool for investigating mental processes is not new. Psychologists such as Jean Piaget and F.C. Bartlett both used stories in research on complex cognitive skills in children and adults. However, with the advent of Ebbinghaus' monumental work on memory using "nonsense syllables," theoretical psychology turned away from the use of meaningful material. With the use of nonsense syllables, researchers hoped to isolate the variables of memory and individual content associations. Recently, there has been a renewal of interest in the study of narrative and memory due to the recognition that narrative taps certain processes that syllables and isolated words do not. In addition, narrative and memory studies have generated interest among those researchers concerned with the applicability of memory studies to educational settings. Disciplines Child Psychology | Cognitive Psychology | Early Childhood Education | Education | Educational Psychology | Language and Literacy Education This review is available at ScholarlyCommons: https://repository.upenn.edu/literacyorg_articles/26 VOL. 22 KEYSTONE FOLKLORE NO. 1-2

Representation and Understanding: Studies in Cognitive Science

https://onlinelibrary.wiley.com/doi/pdf/10.1207/s15516709cog0101_2

Daniel G. Bobrow

Papers

On data-limited and resource-limited processes

The art of metaobject protocol

Beyond the chalkboard: computer support for collaboration and problem solving in meetings

Representation and Understanding: Studies in Cognitive Science

An overview of KRL, a Knowledge Representation Language