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This volume examines the role of logic in cognitive psychology in light of recent developments, such as Gonzalo Reyes's new semantic theory. Chapters reveal the prospects of applying these new theories to cognitive psychology, cognitive science, linguistics, the philosophy of language and logic.
It is a pleasure and an honor to be able to present this collection of papers to Ray Reiter on the occasion of his 60th birthday. To say that Ray's research has had a deep impact on the field of Artificial Intel ligence is a considerable understatement. Better to say that anyone thinking of do ing work in areas like deductive databases, default reasoning, diagnosis, reasoning about action, and others should realize that they are likely to end up proving corol laries to Ray's theorems. Sometimes studying related work makes us think harder about the way we approach a problem; studying Ray's work is as likely to make us want to drop our way of doing things and take up his. This is because more than a mere visionary, Ray has always been a true leader. He shows us how to proceed not by pointing from his armchair, but by blazing a trail himself, setting up camp, and waiting for the rest of us to arrive. The International Joint Conference on Ar tificial Intelligence clearly recognized this and awarded Ray its highest honor, the Research Excellence award in 1993, before it had even finished acknowledging all the founders of the field. The papers collected here sample from many of the areas where Ray has done pi oneering work. One of his earliest areas of application was databases, and this is re flected in the chapters by Bertossi et at. and the survey chapter by Minker.
Cognitive science arose in the 1950s when it became apparent that a number of disciplines, including psychology, computer science, linguistics, and philosophy, were fragmenting. Perhaps owing to the field's immediate origins in cybernetics, as well as to the foundational assumption that cognition is information processing, cognitive science initially seemed more unified than psychology. However, as a result of differing interpretations of the foundational assumption and dramatically divergent views of the meaning of the term information processing, three separate schools emerged: classical cognitive science, connectionist cognitive science, and embodied cognitive science. Examples, cases, and research findings taken from the wide range of phenomena studied by cognitive scientists effectively explain and explore the relationship among the three perspectives. Intended to introduce both graduate and senior undergraduate students to the foundations of cognitive science, Mind, Body, World addresses a number of questions currently being asked by those practicing in the field: What are the core assumptions of the three different schools? What are the relationships between these different sets of core assumptions? Is there only one cognitive science, or are there many different cognitive sciences? Giving the schools equal treatment and displaying a broad and deep understanding of the field, Dawson highlights the fundamental tensions and lines of fragmentation that exist among the schools and provides a refreshing and unifying framework for students of cognitive science.
John Pollock aims to construct a theory of rational decision making for real agents--not ideal agents. Real agents have limited cognitive powers, but traditional theories of rationality have applied only to idealized agents that lack such constraints. Pollock argues that theories of ideal rationality are largely irrelevant to the decision making of real agents. Thinking about Acting aims to provide a theory of "real rationality."
Over the past decade, the question of whether there is a mental logic has become subject to considerable debate. There have been attacks by critics who believe that all reasoning uses mental models and return attacks on mental-models theory. This controversy has invaded various journals and has created issues between mental logic and the biases-and-heuristics approach to reasoning, and the content-dependent theorists. However, despite its pertinence to current issues in cognition, few cognitive scientists really know what the mental-logic theory is, and misapprehensions are prevalent. This volume is a comprehensive presentation of the theory of mental logic and its implications for cognition and development, including the acquisition of language. The theory offered here has three parts. Part I is the mental logic per se that contains a set of inference schemas. Part II is a reasoning program that applies the schemas in lines of reasoning, including a direct-reasoning routine and more sophisticated indirect-reasoning strategies. Part III of the theory is pragmatic, proposing that the basic meaning of each logic particle is in the inferences that are sanctioned by its inference schemas.
A wide-ranging collection of essays inspired by the memory of the cognitive psychologist John Macnamara.
Metacognition refers to the awareness an individual has of their own mental processes (also referred to as ' thinking about thinking'). In the past thirty years metacognition research has become a rapidly growing field of interdisciplinary research within the cognitive sciences. Just recently, there have been major changes in this field, stimulated by the controversial issues of metacognition in nonhuman animals and in early infancy. Consequently the question what defines a metacognitive process has become a matter of debate: how should one distinguish between simple minds that are not yet capable of any metacognitive processing, and minds with a more advanced architecture that exhibit such a capacity? Do nonhuman animals process the ability to monitor their own mental actions? If metacognition is unique to humans, then at what stage in development does it occur, and how can we distinguish between cognitive and metacognitive processes? The Foundations of Metacognition brings together leading cognitive scientists to consider these questions. It explores them from three different perspectives: from an evolutionary point of view the authors ask whether there is sufficient evidence that some non-human primates or other animals monitor their mental states and thereby exhibit a form of metacognition. From a developmental perspective the authors ask when children start to monitor, evaluate und control their own minds. And from a philosophical point of view the main issue is how to draw the line between cognitive and metacognitive processes, and how to integrate the different functions in which metacognition is involved into a single coherent picture of the mind. The foundations of metacognition - whatever they will turn out to be - have to be as complex as this pattern of connections we discover in its effects. Bringing together researchers from across the cognitive sciences, the book is valuable for philosophers of mind, developmental and comparative psychologists, and neuroscientists.
The purpose of the book is to advance in the understanding of brain function by defining a general framework for representation based on category theory. The idea is to bring this mathematical formalism into the domain of neural representation of physical spaces, setting the basis for a theory of mental representation, able to relate empirical findings, uniting them into a sound theoretical corpus. The innovative approach presented in the book provides a horizon of interdisciplinary collaboration that aims to set up a common agenda that synthesizes mathematical formalization and empirical procedures in a systemic way. Category theory has been successfully applied to qualitative analysis, mainly in theoretical computer science to deal with programming language semantics. Nevertheless, the potential of category theoretic tools for quantitative analysis of networks has not been tackled so far. Statistical methods to investigate graph structure typically rely on network parameters. Category theory can be seen as an abstraction of graph theory. Thus, new categorical properties can be added into network analysis and graph theoretic constructs can be accordingly extended in more fundamental basis. By generalizing networks using category theory we can address questions and elaborate answers in a more fundamental way without waiving graph theoretic tools. The vital issue is to establish a new framework for quantitative analysis of networks using the theory of categories, in which computational neuroscientists and network theorists may tackle in more efficient ways the dynamics of brain cognitive networks. The intended audience of the book is researchers who wish to explore the validity of mathematical principles in the understanding of cognitive systems. All the actors in cognitive science: philosophers, engineers, neurobiologists, cognitive psychologists, computer scientists etc. are akin to discover along its pages new unforeseen connections through the development of concepts and formal theories described in the book. Practitioners of both pure and applied mathematics e.g., network theorists, will be delighted with the mapping of abstract mathematical concepts in the terra incognita of cognition.
This volume on the semantic complexity of natural language explores the question why some sentences are more difficult than others. While doing so, it lays the groundwork for extending semantic theory with computational and cognitive aspects by combining linguistics and logic with computations and cognition. Quantifier expressions occur whenever we describe the world and communicate about it. Generalized quantifier theory is therefore one of the basic tools of linguistics today, studying the possible meanings and the inferential power of quantifier expressions by logical means. The classic version was developed in the 1980s, at the interface of linguistics, mathematics and philosophy. Before this volume, advances in "classic" generalized quantifier theory mainly focused on logical questions and their applications to linguistics, this volume adds a computational component, the third pillar of language use and logical activity. This book is essential reading for researchers in linguistics, philosophy, cognitive science, logic, AI, and computer science.
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