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What Is Mind Design? | |
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Perspectives and things | |
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The Turing test | |
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Intentionality | |
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Original intentionality | |
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Computers | |
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Formal systems | |
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Automatic formal systems | |
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Computers and intelligence | |
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GOFAI | |
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Interpreted formal systems | |
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Intelligence by explicit reasoning | |
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New-fangled Al | |
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Connectionist networks | |
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Embodied and embedded Al | |
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What's missing from mind design? | |
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Notes | |
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Computing Machinery and Intelligence | |
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The imitation game | |
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Critique of the new problem | |
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The machines concerned in the game | |
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Digital computers | |
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Universality of digital computers | |
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Contrary views on the main question | |
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Learning machines | |
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Notes | |
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True Believers: The Intentional Strategy and Why It Works | |
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The intentional strategy and how it works | |
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True believers as intentional systems | |
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Why does the intentional strategy work? | |
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Notes | |
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Computer Science as Empirical Inquiry: Symbols and Search | |
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Symbols and physical symbol systems | |
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Laws of qualitative structure | |
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Physical symbol systems | |
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Development of the symbol-system hypothesis | |
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The evidence | |
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Conclusion | |
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Heuristic search | |
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Problem Solving | |
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Search in problem solving | |
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Intelligence without much search | |
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Conclusion | |
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A Framework for Representing Knowledge | |
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Frames | |
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Artificial intelligence and human problem solving | |
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Default assignment | |
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Language, understanding, and scenarios | |
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Words, sentences, and meanings | |
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Scenarios | |
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Scenarios and "questions" | |
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Questions, systems, and cases | |
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Learning, memory, and paradigms | |
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Requests to memory | |
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Excuses | |
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Clusters, classes, and a geographic analogy | |
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Analogies and alternative descriptions | |
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Frames and paradigms | |
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Appendix: criticism of the logistic approach | |
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From Micro-Worlds to Knowledge Representation: AI at an Impasse | |
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The early seventies: micro-worlds | |
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SHRDLU: understanding natural language | |
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"Scene parsing" and computer vision | |
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Learning new concepts or categories | |
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The later seventies: knowledge representation | |
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Frames and knowledge representation | |
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Scripts and primitive actions | |
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KRL: a knowledge-representation language | |
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Conclusion | |
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Notes | |
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Minds, Brains, and Programs | |
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Notes | |
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The Architecture of Mind: A Connectionist Approach | |
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Why brain-style computation? | |
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The connectionist framework | |
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Computational features of connectionist models | |
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The state of the art | |
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Some architecture | |
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The scaling problem | |
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The generalization problem | |
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Connectionist Modeling: Neural Computation / Mental Connections | |
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Levels of analysis: neural and mental structures | |
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The symbolic paradigm | |
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The subsymbolic paradigm | |
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Semantic interpretation | |
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The subsymbolic level | |
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Subsymbolic computation | |
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Subsymbolic inference and the statistical connection | |
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Higher-level descriptions | |
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The best-fit principle | |
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Productions, sequential processing, and logical inference | |
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The dynamics of activation patterns | |
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Schemata | |
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Conclusion | |
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On the Nature of Theories: A Neurocomputational Perspective | |
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The classical view of theories | |
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Problems and alternative approaches | |
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Elementary brainlike networks | |
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Representation and learning in brainlike networks | |
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Some functional properties of brainlike networks | |
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How faithfully do these networks depict the brain? | |
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Computational neuroscience: the naturalization of epistemology | |
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Concluding remarks | |
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Connectionism and Cognition | |
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Notes | |
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Connectionism and Cognitive Architecture: A Critical Analysis | |
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Introduction | |
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Levels of explanation | |
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The nature of the dispute | |
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Complex mental representations | |
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Representations as "distributed" over microfeatures | |
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Structure-sensitive operations | |
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Learning | |
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Reasoning | |
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The need for symbol systems: productivity, systematicity, and inferential coherence | |
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Productivity of thought | |
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Systematicity of cognitive representation | |
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The systematicity of inference | |
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Summary | |
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The allure of connectionism | |
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Replies: why the usual reasons given for preferring a connectionist architecture are invalid | |
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Parallel computation and the issue of speed | |
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Resistance to noise and physical damage (and the argument for distributed representation) | |
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"Soft" constraints, continuous magnitudes, and stochastic mechanisms | |
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Explicitness of rules | |
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On "brain-style" modeling | |
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Concluding comments: connectionism as a theory of implementation | |
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Conclusion | |
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Notes | |
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Connectionism, Eliminativism, and the Future of Folk Psychology | |
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Introduction | |
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Eliminativism and folk psychology | |
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Propositional attitudes and common-sense psychology | |
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A family of connectionist hypotheses | |
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A connectionist model of memory | |
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Objections and replies | |
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Conclusion | |
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Notes | |
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The Presence of a Symbol | |
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A slippery LOT | |
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The pocket Fodor | |
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On being more explicit | |
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Connectionism and explicit representation | |
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Code-fixation: its symptoms and cure | |
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All the world's a processor | |
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Conclusions: from code to process | |
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Notes | |
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Intelligence without Representation | |
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Introduction | |
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The evolution of intelligence | |
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A story | |
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Abstraction as a dangerous weapon A continuing story | |
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Incremental intelligence | |
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Decomposition by function | |
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Decomposition by activity | |
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Who has the representations? | |
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No representation versus no central representation | |
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The methodology in practice | |
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Methodological maxims | |
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An instantiation of the methodology: Allen | |
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A second example: Herbert | |
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What this is not | |
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It isn't connectionism | |
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It isn't neural networks | |
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It isn't production rules | |
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It isn't a blackboard | |
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It isn't German philosophy | |
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Key ideas | |
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Situatedness | |
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Embodiment | |
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Intelligence | |
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Emergence | |
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Limits to growth | |
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Dynamics and Cognition | |
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The governing problem | |
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Two kinds of governor | |
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Conceptual frameworks | |
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Morals | |
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Three kinds of system | |
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Three conceptions of cognition | |
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An example of dynamical research | |
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Is the dynamical conception viable? | |
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Notes | |
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Acknowledgments | |
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Bibliography | |