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1.19 MB
Extraction Summary
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Document Information
Type:
Scientific paper / academic text / government evidence production
File Size:
1.19 MB
Summary
This document appears to be page 79 of a scientific text or academic paper regarding Artificial Intelligence and cognitive architectures. It specifically details section 4.5.1 regarding the 'CLARION' architecture developed by Ron Sun, comparing it to other systems like Soar and ACT-R. The document bears a 'HOUSE_OVERSIGHT_012995' stamp, indicating it was part of a document production for a US House Oversight Committee investigation (likely related to Epstein's funding of scientific research, though Epstein is not explicitly named on this page).
People (1)
| Name | Role | Context |
|---|---|---|
| Ron Sun | Researcher/Author |
Creator of the CLARION cognitive architecture mentioned in the text.
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Organizations (7)
| Name | Type | Context |
|---|---|---|
| House Oversight Committee |
Implied by the Bates stamp 'HOUSE_OVERSIGHT_012995' at the bottom of the page.
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| CLARION |
The primary subject of the text section.
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| CogPrime |
Mentioned as being inspired by LIDA and MicroPsi.
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| LIDA |
Mentioned as an inspiration for CogPrime.
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| MicroPsi |
Mentioned as an inspiration for CogPrime.
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| Soar |
Mentioned as a comparative architecture limited to explicit knowledge.
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| ACT-R |
Mentioned as a comparative architecture limited to explicit knowledge.
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Key Quotes (3)
"Ron Sun’s CLARION architecture (see Figure 4.9) is interesting in its combination of symbolic and neural aspects"Source
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Quote #1
"From a CLARION perspective, architectures like Soar and ACT-R are severely limited in that they deal only with explicit knowledge and associated learning processes."Source
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Quote #2
"CLARION consists of a number of distinct subsystems, each of which contains a dual representational structure"Source
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Quote #3
Full Extracted Text
Complete text extracted from the document (1,770 characters)
4.5 Globalist versus Localist Representations 79
properties could be manifested by AI systems. Rigorously studying the corpus of existing (or hypothetical!) cognitive architectures using these ideas would be a large task, which we do not undertake here.
In the next sections we review several hybrid architectures in more detail, focusing most deeply on LIDA and MicroPsi which have been directly inspirational for CogPrime.
In the next sections we review several hybrid architectures in more detail, focusing most deeply on LIDA and MicroPsi which have been directly inspirational for CogPrime.
4.5.1 CLARION
Ron Sun’s CLARION architecture (see Figure 4.9) is interesting in its combination of symbolic and neural aspects – a combination that is used in a sophisticated way to embody the distinction and interaction between implicit and explicit mental processes. From a CLARION perspective, architectures like Soar and ACT-R are severely limited in that they deal only with explicit knowledge and associated learning processes.
CLARION consists of a number of distinct subsystems, each of which contains a dual representational structure, including a “rules and chunks” symbolic knowledge store somewhat similar to ACT-R, and a neural net knowledge store embodying implicit knowledge. The main subsystems are:
CLARION consists of a number of distinct subsystems, each of which contains a dual representational structure, including a “rules and chunks” symbolic knowledge store somewhat similar to ACT-R, and a neural net knowledge store embodying implicit knowledge. The main subsystems are:
• An action-centered subsystem to control actions;
• A non-action-centered subsystem to maintain general knowledge;
• A motivational subsystem to provide underlying motivations for perception, action, and cognition;
• A meta-cognitive subsystem to monitor, direct, and modify the operations of all the other subsystems.
• A non-action-centered subsystem to maintain general knowledge;
• A motivational subsystem to provide underlying motivations for perception, action, and cognition;
• A meta-cognitive subsystem to monitor, direct, and modify the operations of all the other subsystems.
Top Level
action-centered explicit representation
non-action-centered explicit representation
action-centered-implicit representation
non-action-centered implicit representation
Bottom Level
action-centered explicit representation
non-action-centered explicit representation
action-centered-implicit representation
non-action-centered implicit representation
Bottom Level
Fig. 4.9: The CLARION cognitive architecture.
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