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| Title: | Development of a Large-Scale Integrated Neurocognitive Architecture Part 1: Conceptual Framework |
| Authors: | Reggia, James A.
Tagamets, Malle
Contreras-Vidal, Jose
Weems, Scott
Jacobs, David
Winder, Ransom
Chabuk, Timur |
| Type: | Technical Report |
| Issue Date: | 15-Jun-2006 |
| Series/Report no.: | UM Computer Science Department
CS-TR-4814
UMIACS
UMIACS-TR-2006-33 |
| Abstract: | The idea of creating a general purpose machine intelligence that captures
many of the features of human cognition goes back at least to the earliest days
of artificial intelligence and neural computation. In spite of more than a
half-century of research on this issue, there is currently no existing approach
to machine intelligence that comes close to providing a powerful, general-purpose
human-level intelligence. However, substantial progress made during recent years
in neural computation, high performance computing, neuroscience and cognitive
science suggests that a renewed effort to produce a general purpose and adaptive
machine intelligence is timely, likely to yield qualitatively more powerful
approaches to machine intelligence than those currently existing, and certain
to lead to substantial progress in cognitive science, AI and neural computation.
In this report, we outline a conceptual framework for the long-term development
of a large-scale machine intelligence that... |
| URI: | http://hdl.handle.net/1903/3665 |
| Appears in Collections: | Technical Reports from UMIACS
Technical Reports of the Computer Science Department
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Files in This Item:
| File |
Description |
Size | Format | No. of Downloads |
|---|
| MarylandPart1.pdf | | 2060Kb | Adobe PDF | 564 | View/Open |
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