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ake c to denote algorithmic information measured on some reference Turing machine, and F(X) to denote what appears on the second tape of a two-tape Turing machine t time-steps after placing X on its first tape. Other more naturalistic computational models are also possible here and are discussed extens
rithms carrying out separate functions, encapsulated in black boxes and communicating results with each other." For instance, PolyScheme, ACT-R and CLARION all display this "modularity" property to a significant extent. These architectures lack the rich, real-time interaction between the intents/ dynam
w 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
take c to denote algorithmic information measured on some reference Turing machine, and F(X) to denote what appears on the second tape of a two-tape Turing machine ¢ time-steps after placing X on its first tape. Other more naturalistic computational models are also possible here and are discussed extensi
intelligence will involve a combination of symbolic and non-symbolic processing.” A few of the more important hybrid cognitive architectures are: ¢ CLARION [SZ04] is a hybrid architecture that combines a symbolic component for reason- ing on “explicit knowledge” with a connectionist component for managin
already encompassed by Legg and Hutter’s definition because one may bias the distribution of environments within the latter by considering different Turing machines underlying the Kolmogorov complexity. However this is not a general equivalence because the Solomonoff-Levin measure intrinsically HOUSE_OV
chematics and production rules or other similar constructs, is that in CogPrime this level of knowledge representation is not the only important one. CLARION [SZ04], as reviewed above, is an example of a cognitive architecture that uses production rules for explicit knowledge representation and then uses a
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