Book•
Human Associative Memory
01 Jan 1973-
TL;DR: In this paper, a theory about human memory, about how a person encodes, retains, and retrieves information from memory, was proposed and tested, based on the HAM theory.
Abstract: Published in 1980, part of the Experimental Psychology series. This book proposes and tests a theory about human memory, about how a person encodes, retains, and retrieves information from memory. This edition contains two major parts. First is the historical analysis of associationism and its countertraditions. This still provides the framework that has been used to relate the current research to an important intellectual tradition. This is reproduced without comment from the original book; historical analyses do not need as rapid revision as theoretical analyses. The second part of the book reproduces the major components of the HAM theory.
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TL;DR: The present paper shows how the extended theory can account for results of several production experiments by Loftus, Juola and Atkinson's multiple-category experiment, Conrad's sentence-verification experiments, and several categorization experiments on the effect of semantic relatedness and typicality by Holyoak and Glass, Rips, Shoben, and Smith, and Rosch.
Abstract: This paper presents a spreading-acti vation theory of human semantic processing, which can be applied to a wide range of recent experimental results The theory is based on Quillian's theory of semantic memory search and semantic preparation, or priming In conjunction with this, several of the miscondeptions concerning Qullian's theory are discussed A number of additional assumptions are proposed for his theory in order to apply it to recent experiments The present paper shows how the extended theory can account for results of several production experiments by Loftus, Juola and Atkinson's multiple-category experiment, Conrad's sentence-verification experiments, and several categorization experiments on the effect of semantic relatedness and typicality by Holyoak and Glass, Rips, Shoben, and Smith, and Rosch The paper also provides a critique of the Smith, Shoben, and Rips model for categorization judgments Some years ago, Quillian1 (1962, 1967) proposed a spreading-acti vation theory of human semantic processing that he tried to implement in computer simulations of memory search (Quillian, 1966) and comprehension (Quillian, 1969) The theory viewed memory search as activation spreading from two or more concept nodes in a semantic network until an intersection was found The effects of preparation (or priming) in semantic memory were also explained in terms of spreading activation from the node of the primed concept Rather than a theory to explain data, it was a theory designed to show how to build human semantic structure and processing into a computer
7,586 citations
Cites background from "Human Associative Memory"
...Perhaps the most prevalent misinterpretation of Quillian's theory concerns the idea of cognitive economy (Anderson & Bower, 1973; Conrad, 1972)....
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...Anderson and Bower (1973) reject a Quillian-like model of a parallel search, while acknowledging that their data are compatible with "a parallel model whose search rate is slower in proportion to the number of paths that must be searched" (p. 371)....
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7,489 citations
TL;DR: Tested the 2-process theory of detection, search, and attention presented by the current authors (1977) in a series of experiments and demonstrated the qualitative difference between 2 modes of information processing: automatic detection and controlled search.
Abstract: Tested the 2-process theory of detection, search, and attention presented by the current authors (1977) in a series of experiments. The studies (a) demonstrate the qualitative difference between 2 modes of information processing: automatic detection and controlled search; (b) trace the course of the
7,032 citations
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TL;DR: Experiments in which happy or sad moods were induced in subjects by hyp- notic suggestion to investigate the influence of emo- tions on memory and thinking found that subjects exhibited mood-state-dependent memory in recall of word lists, personal experiences recorded in a daily diary, and childhood experiences.
Abstract: This article describes experiments in which happy or sad moods were induced in subjects by hyp- notic suggestion to investigate the influence of emo- tions on memory and thinking. One result was that subjects exhibited mood-state-dependent memory in recall of word lists, personal experiences recorded in a daily diary, and childhood experiences; people recalled a greater percentage of those experiences that were affectively congruent with the mood they were in dur- ing recall. Second, emotion powerfully influenced such cognitive processes as free associations, imaginative fantasies, social perceptions, and snap judgments about others' personalities (e.g., angry subjects generated an- gry associates, told hostile stories, and were prone to find fault with others). Third, when the feeling-tone of a narrative agreed with the reader's emotion, the salience and memorability of events in that narrative were increased. Thus, sad readers attended more to sad material, identified with a sad character from a story, and recalled more about that character. An associative network theory is proposed to account for these several results. In this theory, an emotion serves as a memory unit that can enter into associations with coincident events. Activation of this emotion unit aids retrieval of events associated with it; it also primes emotional themata for use in free association, fantasies, and per- ceptual categorization.
5,724 citations
Cites background from "Human Associative Memory"
...Examples of network theories appear in papers or books by Collins and Quillian (1969), Anderson and Bower (1973), Collins and Loftus (1975), and Anderson (1976)....
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TL;DR: A perceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal symbol systems and implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.
Abstract: Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components - not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.
5,259 citations
Cites background from "Human Associative Memory"
...Another important lesson that we have learned from amodal symbol systems is that a viable theory of knowledge must implement propositions that describe and interpret situations (e.g., Anderson & Bower 1973; Goodman 1976; Kintsch 1974; Norman et al. 1975; Pylyshyn 1973; 1978; 1981; 1984)....
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Book•
01 Jan 1972TL;DR: A computer system for understanding English that contains a parser, a recognition grammar of English, programs for semantic analysis, and a general problem solving system based on the belief that in modeling language understanding, it must deal in an integrated way with all of the aspects of language—syntax, semantics, and inference.
Abstract: This paper describes a computer system for understanding English. The system answers questions, executes commands, and accepts information in an interactive English dialog. It is based on the belief that in modeling language understanding, we must deal in an integrated way with all of the aspects of language—syntax, semantics, and inference. The system contains a parser, a recognition grammar of English, programs for semantic analysis, and a general problem solving system. We assume that a computer cannot deal reasonably with language unless it can understand the subject it is discussing. Therefore, the program is given a detailed model of a particular domain. In addition, the system has a simple model of its own mentality. It can remember and discuss its plans and actions as well as carrying them out. It enters into a dialog with a person, responding to English sentences with actions and English replies, asking for clarification when its heuristic programs cannot understand a sentence through the use of syntactic, semantic, contextual, and physical knowledge. Knowledge in the system is represented in the form of procedures, rather than tables of rules or lists of patterns. By developing special procedural representations for syntax, semantics, and inference, we gain flexibility and power. Since each piece of knowledge can be a procedure, it can call directly on any other piece of knowledge in the system.
2,441 citations