Epstein Secrets

Perspective on Development. MIT Press, 1997. Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. PF92. Christian Freksa and Robert Milton. Temporal reasoning based on semi-intervals. Artificial Intel- ligence, 54(1-2):199 - 227, 1992

, 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

Press, 1997. EFTA00624120 References 345 Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. Elm91. J. Elman. Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning, 7:195-226, 1991.

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

, 1997. HOUSE_OVERSIGHT_013260 References 345 Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. Elm91. J. Elman. Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning, 7:195-226, 1991. E

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