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The Atomic Components of Thought
TLDR
The preface to the book describes how C.R. Anderson's Cognitive Arithmetic transformed into Knowledge Representation and how M. Lovett's choice changed the way that people viewed the world around them.
An integrated theory of the mind.
TLDR
The perceptual-motor modules, the goal module, and the declarative memory module are presented as examples of specialized systems in ACT-R, which consists of multiple modules that are integrated to produce coherent cognition.
The Cascade-Correlation Learning Architecture
TLDR
The Cascade-Correlation architecture has several advantages over existing algorithms: it learns very quickly, the network determines its own size and topology, it retains the structures it has built even if the training set changes, and it requires no back-propagation of error signals through the connections of the network.
A choice prediction competition: Choices from experience and from description
TLDR
The best predictions of decisions from descriptions were obtained with a stochastic variant of prospect theory assuming that the distance to the weighted values decreases with the distance between the cumulative payoff functions.
An integrated theory of list memory.
The ACT-R theory (Anderson, 1993; Anderson & Lebiere, 1998) is applied to the list memory paradigms of serial recall, recognition memory, free recall, and implicit memory. List memory performance in
ACT-R: A Theory of Higher Level Cognition and Its Relation to Visual Attention
TLDR
A demonstration of ACT-R's application to menu selection is discussed and it is shown that theACT-R theory makes unique predictions, without estimating any parameters, about the time to search a menu.
The Newell Test for a theory of cognition
TLDR
12 criteria that the human cognitive architecture would have to satisfy in order to be functional are distilled into 12 criteria: flexible behavior, real-time performance, adaptive behavior, vast knowledge base, dynamic behavior, knowledge integration, natural language, learning, development, evolution, and brain realization.
A Standard Model of the Mind: Toward a Common Computational Framework across Artificial Intelligence, Cognitive Science, Neuroscience, and Robotics
TLDR
A key foundational hypothesis in artificial intelligence is that minds are computational entities of a special sort — that is, cognitive systems — that can be implemented through a diversity of physical devices, whether natural brains, traditional generalpurpose computers, or other sufficiently functional forms of hardware or wetware.
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