Epstein Secrets

ion. PhD thesis, MIT, 1998. ZHIO. Ruoyu Zou and Lawrence B. Holder. Frequent subgraph mining on a single l

, 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

t Thought, volume 2. pages 63-78. 1990. KLH8.3. Lawrence Kohlberg, Charles Levine, and Alexandra Hewer. Mo

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

ult Thought, volume 2, pages 63-78. 1990. KLH83. Lawrence Kohlberg, Charles Levine, and Alexandra Hewer. Mo

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