Epstein Secrets

re learning" - it's not actually a procedure learning process, but rather a process that utilizes the fruits of procedure learning. The well-known "Occam's razor" heuristic says that all else being equal, simpler is better. This notion is embodied mathematically in the Solomonoff-Levin "universal prio

on an Alternative Representational Approach We briefly pause to contrast certain technical aspects of the present approach to analogous as- pects of the Webmind AI Engine (one of CogPrime's predecessor Al systems, briefly discussed in Chapter 19.1). This predecessor system used a knowledge representation somewhat simi

have come to the following conclusions: • for relatively straightforward procedure learning problems, hilldimbing with random restart and a strong Occam bias is an effective method • for more difficult problems that elude hinclimbing, probabilistic evolutionary program learn- Mg is an effective metho

eferences in the listener's mind. • Psynet Model: An early version of the theory of mind underlying CogPrime, referred to in some early writings on the Webmind AI Engine and Novamente Cognition Engine. The concepts underlying the psynet model are still part of the theory underlying CogPrime, but the name has been de

ne effective approach to evolu- tionary program learning. MOSES is one good realization of this approach. e. Multistart hill-climbing, with a strong Occam prior, is a good way to handle relatively straightforward program learning problems. f. Activation spreading and Hebbian learning comprise a reason

fore anyone else was interested in listening. Ken and I schemed some AGI designs at Simon's Rock College in 1983, years before we worked together on the Webmind AI Engine. • Allan Combs, who got me thinking about consciousness in various different ways, at a very early point in my career. I'm very pleased to still co

ne effective approach to evolu- tionary program learning. MOSES is one good realization of this approach. e. Multistart hill-climbing, with a strong Occam prior, is a good way to handle relatively straightforward program learning problems. f. Activation spreading and Hebbian learning comprise a reasona

oing thinking and research). The collaborative design process ultimately resulting in CogPrime started in 1997 when Intelligenesis Corp. was formed — the Webmind AI Engine created in Intelligenesis’s research group during 1997-2001 was the predecessor to the Novamente Cognition Engine created at Novamente LLC during 200