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e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con
cision graph looks like: Input: List L Output: List If ( P1 (L) ) N1(L) Else If ( P2 (L) ) N2 (L) Else If ( Pk (L) ) Nk(L) EFTA00624098 18.4 Self-Modification via Theorem-Proving 323 where the Pi are predicates, and the Ni are schemata corresponding to other nodes of the decision graph (children of the c
e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con
, ImplicationLink, etc.) or a fuzzy value (as in MemberLink, EvaluationLink). • Strong Self-Modification: This is generally used as synonymous with Self-Modification, in a CogPrime context. • Subsymbolic: Involving processing of data using elements that have no correspondence to natural language terms, nor abst
e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. CIM-Dynamic: Concr
nt decision graphs. The decision graph leading to maximal optimization, may not be the one that leads CogPrime cognition in optimal directions. 18.4 Self-Modification via Theorem-Proving Supercompilation is a potentially very valuable tool for self-modification. If one wants to take an existing schema and graduall
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