The book will serve as an excellent graduate-level textbook in cognitive psychology, linguistics, and artificial intelligence.

The now-classic Metaphors We Live By changed our understanding of metaphor and its role in language and the mind. Metaphor, the authors explain, is a fundamental mechanism of mind, one that allows us to use what we know about our physical and social experience to provide understanding of countless other subjects. Because such metaphors structure our most basic understandings of our experience, they are "metaphors we live by"--metaphors that can shape our perceptions and actions without our ever noticing them. In (...) this updated edition of Lakoff and Johnson's influential book, the authors supply an afterword surveying how their theory of metaphor has developed within the cognitive sciences to become central to the contemporary understanding of how we think and how we express our thoughts in language. (shrink)

Mental Spaces is the classic introduction to the study of mental spaces and conceptual projection, as revealed through the structure and use of language. It examines in detail the dynamic construction of connected domains as discourse unfolds. The discovery of mental space organization has modified our conception of language and thought: powerful and uniform accounts of superficially disparate phenomena have become available in the areas of reference, presupposition projection, counterfactual and analogical reasoning, metaphor and metonymy, and time and aspect in (...) discourse. The present work lays the foundation for this research. It uncovers simple and general principles that lie behind the awesome complexity of everyday logic. (shrink)

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. (shrink)

This work uses counterfactual conjectures to draw inferences from historical data. It proposes criteria for evaluating counterfactuals that occur in diverse methodological contexts including: comparative case studies; game theory; and statistical analysis.

Keith Holyoak and Paul Thagard provide a unified, comprehensive account of the diverse operations and applications of analogy, including problem solving, ...

A theory of analogy must describe how the meaning of an analogy is derived from the meanings of its parts. In the structure‐mapping theory, the interpretation rules are characterized as implicit rules for mapping knowledge about a base domain into a target domain. Two important features of the theory are (a) the rules depend only on syntactic properties of the knowledge representation, and not on the specific content of the domains; and (b) the theoretical framework allows analogies to be distinguished (...) cleanly from literal similarity statements, applications of abstractions, and other kinds of comparisons.Two mapping principles are described: (a) Relations between objects, rather than attributes of objects, are mapped from base to target; and (b) The particular relations mapped are determined by systematicity, as defined by the existence of higher‐order relations. (shrink)

We suggest a common ground for alternative proposals In different domains of cognitive science which have previously seemed to have little in common. The underlying common theme is associated with a redefinition of the basic unit of analysis in each domain of thought. Our framework suggests a definition of unity which is based not on inherent properties of the elements constituting the unit, but rather on dynamic patterns of correlation across the elements. We introduce a set of features that characterize (...) the new dynamic units, and distinguish them from traditional units of analysis. A conceptual connection is made with the identification of elementary units in modern physics theories, as well as with concepts and structures in the study of complex dynamical systems and connectionism. The paper analyses the evolution of the concept of unit in different domains of thought in cognitive science, and examines the proposed framework of “dynamic unity” with regard to various theoretical problems within each domain. The particular cognitive science issues discussed in the paper include: (1) the binding problem in the brain; (2) the mental unit of conceptual organization; (3) defining ‘wordhood’ in linguistics; and (4) identifying the unit of cognition in the natural environment. (shrink)

We usually consider literary thinking to be peripheral and dispensable, an activity for specialists: poets, prophets, lunatics, and babysitters. Certainly we do not think it is the basis of the mind. We think of stories and parables from Aesop's Fables or The Thousand and One Nights, for example, as exotic tales set in strange lands, with spectacular images, talking animals, and fantastic plots--wonderful entertainments, often insightful, but well removed from logic and science, and entirely foreign to the world of everyday (...) thought. But Mark Turner argues that this common wisdom is wrong. The literary mind--the mind of stories and parables--is not peripheral but basic to thought. Story is the central principle of our experience and knowledge. Parable--the projection of story to give meaning to new encounters--is the indispensable tool of everyday reason. Literary thought makes everyday thought possible. This book makes the revolutionary claim that the basic issue for cognitive science is the nature of literary thinking. In The Literary Mind, Turner ranges from the tools of modern linguistics, to the recent work of neuroscientists such as Antonio Damasio and Gerald Edelman, to literary masterpieces by Homer, Dante, Shakespeare, and Proust, as he explains how story and projection--and their powerful combination in parable--are fundamental to everyday thought. In simple and traditional English, he reveals how we use parable to understand space and time, to grasp what it means to be located in space and time, and to conceive of ourselves, other selves, other lives, and other viewpoints. He explains the role of parable in reasoning, in categorizing, and in solving problems. He develops a powerful model of conceptual construction and, in a far-reaching final chapter, extends it to a new conception of the origin of language that contradicts proposals by such thinkers as Noam Chomsky and Steven Pinker. Turner argues that story, projection, and parable precede grammar, that language follows from these mental capacities as a consequence. Language, he concludes, is the child of the literary mind. Offering major revisions to our understanding of thought, conceptual activity, and the origin and nature of language, The Literary Mind presents a unified theory of central problems in cognitive science, linguistics, neuroscience, psychology, and philosophy. It gives new and unexpected answers to classic questions about knowledge, creativity, understanding, reason, and invention. (shrink)

A productive way to think about imagistic mental models of physical systems is as though they were sources of quasi‐empirical evidence. People depict or imagine events at those points in time when they would experiment with the world if possible. Moreover, just as they would do when observing the world, people induce patterns of behavior from the results depicted in their imaginations. These resulting patterns of behavior can then be cast into symbolic rules to simplify thinking about future problems and (...) to reveal higher order relationships. Using simple gear problems, three experiments explored the occasions of use for, and the inductive transitions between, depictive models and number‐based rules. The first two experiments used the convergent evidence of problem‐solving latencies, hand motions, referential language and error data to document the initial use of a model, the induction of rules from the modeling results, and the fallback to a model when a rule fails. The third experiment explored the intermediate representations that facilitate the induction of rules from depictive models. The strengths and weaknesses of depictive modeling and more analytic systems of reasoning are delineated to motivate the reasons for these transitions. (shrink)

Conceptual projection from one mental space to another always involves projection to "middle" spaces-abstract "generic" middle spaces or richer "blended" middle spaces. Projection to a middle space is a general cognitive process, operating uniformly at different levels of abstraction and under superficially divergent contextual circumstances. Middle spaces are indispensable sites for central mental and linguistic work. The process of blending is in particular a fundamental and general cognitive process, running over many (conceivably all) cognitive phenomena, including categorization, the making of (...) hypotheses, inference, the origin and combining of grammatical constructions, analogy, metaphor, and narrative. Blending is not secondary to these phenomena but prerequisite, and its operation is not restricted to any one of these phenomena. We give evidence for blending from a wide range of data that includes everyday language, idioms, literary metaphor, non-verbal conceptualization of action, creative thought in mathematics, evolution of socio-cultural models, jokes, and advertising. Blending is in general invisible to consciousness and detectable only on analysis. Blended spaces are routinely necessary for constructing central meanings, inferences, and structures, and for motivating emotions. We show that the blending of highly schematic spaces yields the fusion of grammatical constructions and functional assemblies studied in Cognitive Grammar and Construction Grammar. Finally, recognizing the cognitive import of middle spaces allows us to propose a generalized four-space model of conceptual projection that subsumes a variety of previous models. We explore the consequences of this model for the theory of concept formation. Introduction 3 I. The four space model 4 II. The phenomenon of blended spaces 5 1. Dante's Inferno 5 2. Regatta 7 3. The riddle of the Buddhist monk 8 4. Getting ahead of oneself 9 5. Tuning in, and other actions 11 6. Complex numbers 12 III. Prototypes of blending and mistaken reductions 14 IV. Further evidence for conceptual projection into a blended space 17 1. President Bush on third base 18 2. President Nixon in France 19 3. Personification 21 V. Category extension 22 VI. Generic spaces 24 VII. Parameters and subschemes 25 VIII. Blending and grammar 30 IX. The concept of a concept 33 Notes 35 References 38. (shrink)

We present a model of similarity‐based retrieval that attempts to capture three seemingly contradictory psychological phenomena: (a) structural commonalities are weighed more heavily than surface commonalities in similarity judgments for items in working memory; (b) in retrieval, superficial similarity is more important than structural similarity; and yet (c) purely structural (analogical) remindings e sometimes experienced. Our model, MAC/FAC, explains these phenomena in terms of a two‐stage process. The first stage uses a computationally cheap, non‐structural matcher to filter candidate long‐term memory (...) items. It uses content vectors, a redundant encoding of structured representations whose dot product estimates how well the corresponding structural representations will match. The second stage uses SME (structure‐mapping engine) to compute structural matches on the handful of items found by the first stage. We show the utility of the MAC/FAC model through a series of computational experiments: (a) We demonstrate that MAC/FAC can model patterns of access found in psychological data; (b) we argue via sensitivity analyses that these simulation results rely on the theory; and (c) we compare the performance of MAC/FAC with ARCS, an alternate model of similarity‐based retrieval, and demonstrate that MAC/FAC explains the data better than ARCS. Finally, we discuss limitations and possible extensions of the model, relationships with other recent retrieval models, and place MAC/FAC in the context of other recent work on the nature of similarity. (shrink)