A Theory of Immediate Awareness: Self-Organization and Adaptation in Natural IntelligenceSpringer Science & Business Media, 29 juin 2013 - 316 pages This book is multi- and interdisciplinary in both scope and content. It draws upon philosophy, the neurosciences, psychology, computer science, and engineering in efforts to resolve fundamental issues about the nature of immediate awareness. Approximately the first half of the book is addressed to historical approaches to the question whether or not there is such a thing as immediate awareness, and if so, what it might be. This involves reviewing arguments that one way or another have been offered as answers to the question or ways of avoiding it. It also includes detailed discussions of some complex questions about the part immediate awareness plays in our over-all natural intelligence. The second half of the book addresses intricate and complex issues involved in the computability of immediate awareness as it is found in simple, ordinary things human beings know how to do, as weIl as in some highly extraordinary things some know how to do. Over the past 2,500 years, human culture has discovered, created, and built very powerful tools for recognizing, classifying, and utilizing patterns found in the natural world. The most powerful of those tools is mathematics, the language of nature. The natural phenomenon of human knowing, of natural intelligence generally, is a very richly textured set of patterns that are highly complex, dynamic, self-organizing, and adaptive. |
Table des matières
THE PROBLEM OF IMMEDIATE AWARENESS | 1 |
ACQUAINTANCE | 33 |
THE CASE | 75 |
WHAT DOES THE EVIDENCE SHOW? | 109 |
AT THE CORE OF MULTIPLE | 159 |
CAN NEURAL NETWORKS SIMULATE BOUNDARY SET S? | 217 |
COMPUTABILITY OF BOUNDARY SET S | 255 |
SUMMARY AND CONCLUSIONS | 279 |
APPENDIX | 291 |
309 | |
Autres éditions - Tout afficher
A Theory of Immediate Awareness: Self-Organization and Adaptation in Natural ... M. Estep Aucun aperçu disponible - 2010 |
Expressions et termes fréquents
abstract algorithm analysis argued arguments attention attractors behavior belief Boolean networks Boundary Set brain characterize classical cognitive complex numbers computational concept consciousness cortex defined descriptions digraph domain dynamic encodable epistemic epistemological example experience found in Boundary function GOFAI graph human knowing images imagining immediate awareness indexicals input kinds of knowing knowing found knowing system knowing the unique knowledge by acquaintance knowledge by description layer learning linguistic logical mathematical meaning mind moral universe Moreover moving and touching natural intelligence natural language natural numbers neural network neurons observation sentence particulars patterns performance philosophy preattentive phase primitive epistemic relations primitive relations probing problem proper names properties proposition Quine Quine's theory recursively enumerable refer relations of immediate representation rule-governed rules Russell Russell's self-organizing sensation sense somatosensory Somatosensory System space stimulations strong AI supervised learning symbolic theoretical theory of knowledge things understanding vector visual