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Daniel C. Dennett

Bio: Daniel C. Dennett is an academic researcher from Tufts University. The author has contributed to research in topics: Consciousness & Philosophy of science. The author has an hindex of 64, co-authored 281 publications receiving 28952 citations. Previous affiliations of Daniel C. Dennett include University of California, Irvine & Center for Advanced Study in the Behavioral Sciences.


Papers
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Book
01 Jan 1987
TL;DR: The Intentional Stance as discussed by the authors is the first full-scale presentation of a theory of intentionality that has been developed for almost twenty years, and it can be seen as a pre-emptive strategy of interpretation that presupposes the rationality of the people or other entities we are hoping to understand and predict.
Abstract: How are we able to understand and anticipate each other in everyday life, in our daily interactions? Through the use of such "folk" concepts as belief, desire, intention, and expectation, asserts Daniel Dennett in this first full-scale presentation of a theory of intentionality that he has been developing for almost twenty years. We adopt a stance, he argues, a predictive strategy of interpretation that presupposes the rationality of the people - or other entities - we are hoping to understand and predict.These principles of radical interpretation have far-reaching implications for the metaphysical and scientific status of the processes referred to by the everday terms of folk psychology and their corresponding terms in cognitive science.While Dennett's philosophical stance has been steadfast over the years, his views have undergone successive enrichments, refinements, and extensions. "The Intentional Stance" brings together both previously published and original material: four of the book's ten chapters - its first and the final three - appear here for the first time and push the theory into surprising new territory. The remaining six were published earlier in the 1980s but were not easily accessible; each is followed by a reflection - an essay reconsidering and extending the claims of the earlier work. These reflections and the new chapters represent the vanguard of Dennett's thought. They reveal fresh lines of inquiry into fundamental issues in psychology, artificial intelligence, and evolutionary theory as well as traditional issues in the philosophy of mind.Daniel C. Dennett is Distinguished Arts and Sciences Professor at Tufts University and the author of "Brainstorms" and "Elbow Room." "The Intentional Stance," along with these works, is a Bradford Book.

4,288 citations

Book
01 Jan 1995
TL;DR: In this groundbreaking and very accessible book, Dennett, the acclaimed author of Consciousness Explained, demonstrates the power of the theory of natural selection and shows how Darwin's great idea transforms and illuminates our traditional view of our place in the universe as discussed by the authors.
Abstract: In this groundbreaking and very accessible book, Daniel C. Dennett, the acclaimed author of Consciousness Explained, demonstrates the power of the theory of natural selection and shows how Darwin's great idea transforms and illuminates our traditional view of our place in the universe. Following Darwinian thinking to its logical conclusions is a risky business, with pitfalls for everybody. Creationists and others who reject evolution are not the only ones to fall into the traps. Many who accept the validity of Darwin's conclusions hesitate before their implications and distort his theory, fearful that it is politically incorrect or antireligious, or that it robs life of all spirituality. Dennett explains the scientific theory of natural selection in vivid terms, and shows how it extends far beyond biology.

2,075 citations

Book
01 Jan 1995
TL;DR: Universal acid is a liquid so corrosive that it will eat through anything as discussed by the authors, and it dissolves glass bottles and stainless-steel canisters as readily as it does paper bags.
Abstract: WHEN I WAS A SCHOOLBOY, MY FRIEND and I used to amuse ourselves with fantasies about an imaginary chemical we called universal acid. I have no idea whether we invented it or inherited it, along with Spanish fly and saltpeter, as part of underground youth culture. Universal acid is a liquid so corrosive that it will eat through anything. The problem with universal acid, of course, is what to keep it in. It dissolves glass bottles and stainless-steel canisters as readily as it does paper bags. What would happen if somehow you came upon a dollop of universal acid? Would the entire planet eventually be destroyed? If not, what would be left? After everything had been transformed by its encounter with universal acid, what would the world look like?

1,465 citations

Book
01 Jan 1978
TL;DR: This book questions the relationship between psychology and morality as well as exploring the concept of human intentionality, and argues that intentional attributes such as desires, goals, beliefs and knowledge are purely mechanistic.
Abstract: A collection of 17 essays exploring the central issues of the philosophy of the mind, and human interaction with psychology and evolutionary biology. This book questions the relationship between psychology and morality as well as exploring the concept of human intentionality. It argues that intentional attributes such as desires, goals, beliefs and knowledge are purely mechanistic. The author also considers the meaning of mental imagery, sensations, pain and other puzzling aspects of consciousness. Central to the discussion of the book is the question of whether psychology can support a vision of humans as moral agents, free to choose what they do and responsible for their actions.

1,209 citations


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Book
01 Jan 1988
TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Abstract: Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability. The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

37,989 citations

Journal ArticleDOI
TL;DR: In this paper, the authors propose a paradigm for managing the dynamic aspects of organizational knowledge creating processes, arguing that organizational knowledge is created through a continuous dialogue between tacit and explicit knowledge.
Abstract: This paper proposes a paradigm for managing the dynamic aspects of organizational knowledge creating processes. Its central theme is that organizational knowledge is created through a continuous dialogue between tacit and explicit knowledge. The nature of this dialogue is examined and four patterns of interaction involving tacit and explicit knowledge are identified. It is argued that while new knowledge is developed by individuals, organizations play a critical role in articulating and amplifying that knowledge. A theoretical framework is developed which provides an analytical perspective on the constituent dimensions of knowledge creation. This framework is then applied in two operational models for facilitating the dynamic creation of appropriate organizational knowledge.

17,196 citations

Journal ArticleDOI
TL;DR: Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents as discussed by the authors ; agent architectures can be thought of as software engineering models of agents; and agent languages are software systems for programming and experimenting with agents.
Abstract: The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents;researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.

6,714 citations

Journal ArticleDOI
TL;DR: A new model of metarepresentational development is used to predict a cognitive deficit which could explain a crucial component of the social impairment in childhood autism.

6,017 citations

01 Jan 1985
TL;DR: In this paper, a new model of metarepresentational development was used to predict a cognitive deficit in children with autism, which could explain a crucial component of the social impairment in childhood autism.
Abstract: Abstract We use a new model of metarepresentational development to predict a cognitive deficit which could explain a crucial component of the social impairment in childhood autism. One of the manifestations of a basic metarepresentational capacity is a ‘theory of mind’. We have reason to believe that autistic children lack such a ‘theory’. If this were so, then they would be unable to impute beliefs to others and to predict their behaviour. This hypothesis was tested using Wimmer and Perner's puppet play paradigm. Normal children and those with Down's syndrome were used as controls for a group of autistic children. Even though the mental age of the autistic children was higher than that of the controls, they alone failed to impute beliefs to others. Thus the dysfunction we have postulated and demonstrated is independent of mental retardation and specific to autism.

6,007 citations