Connectionism and the Philosophy of MindT. Horgan, J. Tienson Springer Science & Business Media, 06.12.2012 - 473 Seiten This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemological aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. One of the most, if not the most, exciting developments within cognitive science has been the emergence of connectionism as an alternative to the computational conception of the mind that tends to dominate the discipline. In this volume, John Tienson and Terence Horgan have brought together a fine collection of stimulating studies on connectionism and its significance. As the Introduction explains, the most pressing questions concern whether or not connectionism can provide a new conception of the nature of mentality. By focusing on the similarities and differences between connectionism and other approaches to cognitive science, the chapters of this book supply valuable resources that advance our understanding of these difficult issues. J.H.F. |
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Seite 16
... example , affirming the consequent , we must suppose that they have propositional attitudes that have consequents . All of the things Rey lists as needing explanation are characterized in common sense intentional terms . But some ...
... example , affirming the consequent , we must suppose that they have propositional attitudes that have consequents . All of the things Rey lists as needing explanation are characterized in common sense intentional terms . But some ...
Seite 31
... example , a decay function can be included so that , without new activation , the activation of a unit drops , and a threshold can be employed such that a unit is not activated unless the input exceeds a certain quantity . A third ...
... example , a decay function can be included so that , without new activation , the activation of a unit drops , and a threshold can be employed such that a unit is not activated unless the input exceeds a certain quantity . A third ...
Seite 33
... example , we treat a system as recognizing a word because so interpreted , its behavior is appropriate . This is how Dennett ( 1978 ) views the attribution of intentional characterizations to any system , ourselves included , and what ...
... example , we treat a system as recognizing a word because so interpreted , its behavior is appropriate . This is how Dennett ( 1978 ) views the attribution of intentional characterizations to any system , ourselves included , and what ...
Seite 39
... example , that their models are much more bio- logically realistic than rule - based models . For example , they point to what is sometimes referred to as the 100 step principle ( Feldman and Ballard , 1982 ) . Given that individual ...
... example , that their models are much more bio- logically realistic than rule - based models . For example , they point to what is sometimes referred to as the 100 step principle ( Feldman and Ballard , 1982 ) . Given that individual ...
Seite 40
... example , it is a natural feature of a connectionist system involved in pattern recognition to be able to respond to deformed inputs or new inputs that are not precisely like those for which it has been designed or to which it has been ...
... example , it is a natural feature of a connectionist system involved in pattern recognition to be able to respond to deformed inputs or new inputs that are not precisely like those for which it has been designed or to which it has been ...
Inhalt
8 | |
CONNECTIONISM VS CLASSICAL | 57 |
JAY G RUECKL Connectionism and the Notion of Levels | 74 |
GARY HATFIELD Representation and RuleInstantiation in | 90 |
GEORGE GRAHAM Connectionism in Pavlovian Harness | 143 |
J CHRISTOPHER MALONEY Connectionism and Conditioning | 167 |
ANDY CLARK Systematicity Structured Representations and | 198 |
GEORGES REY An Explanatory Budget for Connectionism and | 219 |
PAUL SMOLENSKY The Constituent Structure of Connectionist | 281 |
MICHAEL TYE Representation in Pictorialism and | 309 |
JERRY FODOR AND BRIAN P MCLAUGHLIN Connectionism | 331 |
MICHAEL G DYER Connectionism versus Symbolism | 382 |
E BRADSHAW Connectionism and the Specter of | 417 |
GERALD W GLASER Is Perception Cognitively Mediated? | 437 |
Connectionism | 444 |
NAME INDEX | 460 |
TERENCE HORGAN AND JOHN TIENSON Settling into a New | 241 |
DAVID KIRSH Putting a Price on Cognition | 261 |
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activity vectors algorithm analysis animal approach argue argument behavior binding brain C-representation Cambridge characterized classical conditioning Classical constituents Cognitive Architecture cognitive processes cognitive science cognitive system complex compositionality computational computationalism computationalist concepts conditioned stimulus connection weights connectionism connectionist models connectionist networks Connectionist representations connectionist systems constituent structure context cup with coffee described direct realism distinction distributed representations eliminitivist example explain FGREP Fodor and Pylyshyn folk psychology function Hinton human hypothesis identity hypothesis implementation inference input instantiated internal involves language of thought machine manipulation memory mental representations microfeatures mind neural nodes notion object operations output paradigm Parallel Distributed Processing pattern of activation PDP models perception Philosophy position problem properties psychology RCON reason recursive relations represent representationalism Rescorla rule-based Rumelhart script semantic Smolensky Smolensky's suppose symbol processing systematicity tensor product tensor product representation theory Tienson tokens Touretzky unconditioned units variables