Buch, Englisch, 181 Seiten, Paperback, Format (B × H): 170 mm x 242 mm, Gewicht: 339 g
Reihe: Human-centred Systems
Buch, Englisch, 181 Seiten, Paperback, Format (B × H): 170 mm x 242 mm, Gewicht: 339 g
Reihe: Human-centred Systems
ISBN: 978-3-540-19716-4
Verlag: Springer
Connectionism in Context aims to broaden and extend the
debate concerning the significance of connectionist models.
The volume collects together a variety of perspectives by
experimental and developmental psychologists, philosophers
and active AI researchers. These contributions relate con-
nectionist ideas to historical psychlogical debates, e.g.,
over behaviourism and associationism, to develop-
mental and philosophical issues. The result is a volume
which addresses both familiar, but central, topics such as
the relation between connectionism and classical AI, and
less familiar, but highly challenging topics, such as
connectionism,associationism and behaviourism, the dis-
tinction between perception and cognition, the role of en-
vironmental structure, and the potential value ofconnec-
tionism as a means of "symbol grounding". The nine essays
have been written with an interdisciplinary audience in mind
and avoid both technical jargon and heavy mathematics.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Geisteswissenschaften Philosophie Wissenschaftstheorie, Wissenschaftsphilosophie
- Interdisziplinäres Wissenschaften Wissenschaften: Allgemeines Wissenschaften: Theorie, Epistemologie, Methodik
Weitere Infos & Material
1. Introduction.- Architecture and Properties l.- A Copernican Revolution.- Distributed Representations and Context Dependence.- The Nature of Thought.- 2. Action, Connectionism and Enaction: A Developmental Perspective.- Background.- Symbols, Connectionism and Innate Knowledge.- System Scale and the Control of Action.- Development, Emergence and Enaction.- Conclusion.- 3. Connectionism and Why Fodor and Pylyshyn Are Wrong.- The Case Against Connectionism.- What’s Wrong with this Argument.- What’s Wrong with this Defence?.- On Behalf of Neural Networks.- 4. Connectionism, Classical Cognitive Science and Experimental Psychology.- Classicism Versus Connectionism.- The Psychological Data.- Theory.- Modelling.- Conclusions.- 5. Connecting Object to Symbol in Modelling Cognition.- Symbol Systems.- The Symbolic Theory of Mind.- The Symbol Grounding Problem.- Neural Nets.- Transducers and Analogue Transformations.- Robotic Capacities: Discrimination and Identification.- Philosophical Objections to Bottom-Up Grounding of Concrete and Abstract Categories.- Categorical Perception and Category-Learning.- Neural Net and CP.- Analogue Constraints on Symbols.- 6 Active Symbols and Internal Models: Towards a Cognitive Connectionism.- Criticisms of Connectionism.- The Active Symbol.- Higher-Level Processes.- Summary and Concluding Remarks.- 7. Thinking Persons and Cognitive Science.- Extending Content.- The Credentials of Cognition.- Consciousness and What It Is Like.- Conceptualized Content and the Structure of Thinking.- Inference and Causal Systernaticity.- Reconstructing the Mind.- 8. A Brief History of Connectionism and Its Psychological Implications.- Connectionist Assumptions in Earlier Psychologies.- Comparisons of Old and New Connectionism.- Conclusions.- 9. Connectionismand Artificial Intelligence as Cognitive Models.- Artificial Intelligence.- Connectionism.- Classical AI and Connectionism.- 10. The Neural Dynamics of Conversational Coherence.- Previous Research.- A Neurally Inspired Model of Coherence.- Some Experimental Results.- How Associative Is Conversation?.- Final on the Purpose of Conversation.
