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397
The empirical case for two systems of reasoning
, 1996
"... Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations ref ..."
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Cited by 669 (4 self)
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Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations reflect similarity structure and relations of temporal contiguity. The other is “rule based” because it operates on symbolic structures that have logical content and variables and because its computations have the properties that are normally assigned to rules. The systems serve complementary functions and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization.
Distributed representations of structure: A Theory of Analogical Access and Mapping
- PSYCHOLOGICAL REVIEW
, 1997
"... This article describes an integrated theory of analogical access and mapping, instantiated in a ..."
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Cited by 358 (40 self)
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This article describes an integrated theory of analogical access and mapping, instantiated in a
Dual-process models in social and cognitive psychology: Conceptual integration and links to underlying memory systems
- Personality and Social Psychology Review
, 2000
"... On behalf of: ..."
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Conceptual integration networks
- Cognitive Science
, 1998
"... Conceptual integration--"blending"-is a general cognitive operation on a par with analogy, recursion, mental modeling, conceptual categorization, and framing. It serves a variety of cognitive purposes. It is dynamic, supple, and active in the moment of thinking. It yields products that fre ..."
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Cited by 186 (9 self)
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Conceptual integration--"blending"-is a general cognitive operation on a par with analogy, recursion, mental modeling, conceptual categorization, and framing. It serves a variety of cognitive purposes. It is dynamic, supple, and active in the moment of thinking. It yields products that frequently become entrenched in conceptual structure and grammar, and it often performs new work on its previously entrenched products as inputs. Blending is easy to detect in spectacular cases but it is for the most part a routine, workaday process that escapes detection except on technical analysis. It is not resewed for special purposes, and is not costly. In blending, structure from input mental spaces is projected to a separate, "blended " mental space. The proiection is selective. Through completion and elaboration, the blend develops structure not provided by the inputs. Inferences, arguments, and ideas developed in the blend can have effect in cognition, leading us to modify the initial inputs and to change our view of the corresponding situations. Blending operates according to a set of uniform structural and dynamic principles. It additionally observes a set of optimality principles. I. Ih'TRODUCTION Much of the excitement about recent work on language, thought, and action stems from the discovery that the same structural cognitive principles are operating in areas that were once viewed as sharply distinct and technically incommensurable. Under the old view, there were word meanings, syntactic structures, sentence meanings (typically truth-conditional), discourse and pragmatic principles, and then, at a higher level, figures of speech like metaphor and metonymy, scripts and scenarios, rhetoric, forms of inductive and deductive rea-
Processing Capacity Defined by Relational Complexity: Implications for Comparative, Developmental, and Cognitive Psychology
, 1989
"... It is argued that working memory limitations are best defined in terms of the complexity of relations that can be processed in parallel. Relational complexity is related to processing loads in problem solving, and discriminates between higher animal species, as well as between children of differen ..."
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Cited by 182 (14 self)
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It is argued that working memory limitations are best defined in terms of the complexity of relations that can be processed in parallel. Relational complexity is related to processing loads in problem solving, and discriminates between higher animal species, as well as between children of different ages. Complexity is defined by the number of dimensions, or sources of variation, that are related. A unary relation has one argument and one source of variation, because its argument can be instantiated in only one way at a time. A binary relation has two arguments, and two sources of variation, because two argument instantiations are possible at once. Similarly, a ternary relation is three dimensional, a quaternary relation is four dimensional, and so on. Dimensionality is related to number of chunks, because both attributes on dimensions and chunks are independent units of information of arbitrary size. Empirical studies of working memory limitations indicate a soft limit which corresponds to processing one quaternary relation in parallel. More complex concepts are processed by segmentation or conceptual chunking. Segmentation entails breaking tasks into components which do not exceed processing capacity, and which are processed serially. Conceptual chunking entails "collapsing" representations to reduce their dimensionality and consequently their processing load, but at the cost of making some relational information inaccessible. Parallel distributed processing implementations of relational representations show that relations with more arguments entail a higher computational cost, which corresponds to empirical observations of higher processing loads in humans. Empirical evidence is presented that relational complexity discriminates between higher species...
Explorations in creativity
, 1994
"... is provided in screen-viewable form for personal use only by members ..."
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Cited by 153 (1 self)
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is provided in screen-viewable form for personal use only by members
Superstars and me: Predicting the impact of role models on the self
- Journal of Personality and Social Psychology
, 1997
"... The authors propose that superstars are most likely to affect self-views when they are considered relevant. Relevant superstars provoke self-enhancement and inspiration when their success seems attainable but self-deflation when it seems unattainable. Participants ' elf-views were affected only ..."
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Cited by 135 (1 self)
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The authors propose that superstars are most likely to affect self-views when they are considered relevant. Relevant superstars provoke self-enhancement and inspiration when their success seems attainable but self-deflation when it seems unattainable. Participants ' elf-views were affected only when the star's domain of excellence was self-relevant. Relevant stars provoked self-enhancement and inspiration when their success eemed attainable in that participants either still had enough time to achieve comparable success or believed their own abilities could improve over time. Open-ended responses provided rich evidence of inspiration in these circumstances. Relevant stars provoked, if anything, self-deflation when their success eemed unattainable in that participants either had already missed the chance to achieve comparable success or viewed their abilities as fixed and so unlikely to improve. It is a cultural clich6 that superstars, that is, individuals of outstanding achievement, can serve as role models to others, inspiring and motivating them to do their utmost best. To pro-mote such inspiration, prominent women scientists are often invited to address high school girls, eminent African Americans
A symbolic-connectionist theory of relational inference and generalization
- Psychological Review
, 2003
"... The authors present a theory of how relational inference and generalization can be accomplished within a cognitive architecture that is psychologically and neurally realistic. Their proposal is a form of symbolic connectionism: a connectionist system based on distributed representations of concept m ..."
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Cited by 134 (26 self)
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The authors present a theory of how relational inference and generalization can be accomplished within a cognitive architecture that is psychologically and neurally realistic. Their proposal is a form of symbolic connectionism: a connectionist system based on distributed representations of concept meanings, using temporal synchrony to bind fillers and roles into relational structures. The authors present a specific instantiation of their theory in the form of a computer simulation model, Learning and Inference with Schemas and Analogies (LISA). By using a kind of self-supervised learning, LISA can make specific inferences and form new relational generalizations and can hence acquire new schemas by induction from examples. The authors demonstrate the sufficiency of the model by using it to simulate a body of empirical phenomena concerning analogical inference and relational generalization. A fundamental aspect of human intelligence is the ability to form and manipulate relational representations. Examples of relational thinking include the ability to appreciate analogies between seemingly different objects or events (Gentner, 1983; Holyoak & Thagard, 1995), the ability to apply abstract rules in novel situations (e.g., Smith, Langston, & Nisbett, 1992), the ability to understand and learn language (e.g., Kim, Pinker, Prince, & Prasada, 1991), and even the ability to appreciate perceptual similarities
Analog Retrieval by Constraint Satisfaction
- Artificial Intelligence
, 1990
"... We describe a computational model of how analogs are retrieved from memory using simultaneous satisfaction of a set of semantic, structural, and pragmatic constraints. The model is based on psychological evidence suggesting that human memory retrieval tends to favor analogs that have several kinds o ..."
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Cited by 134 (11 self)
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We describe a computational model of how analogs are retrieved from memory using simultaneous satisfaction of a set of semantic, structural, and pragmatic constraints. The model is based on psychological evidence suggesting that human memory retrieval tends to favor analogs that have several kinds of correspondences with the structure that prompts retrieval: semantic similarity, isomorphism, and pragmatic relevance. We describe ARCS, a program that demonstrates how these constraints can be used to select relevant analogs by forming a network of hypotheses and attempting to satisfy the constraints simultaneously. ARCS has been tested on several data bases that display both its psychological plausibility and computational power.
