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fine- ment. In Foundations of Generic Programming. 1999. Row90. John Rowan. Subpersonalities: The People Inside Us. Routledge Press, 1990. RVG05. Mike Ross, Linos Vepstas, and Ben Goertzel. Rolex semantic relationship extractor. http://opencog.org/wilci/RelEx, 2005. EFTA00624680 534 A Glossary Sch
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
able, ambitious, peculiar AGI-oriented firm existed. Special shout-outs to the "Voice of Reason" Pei Wang and the "Siberian Madmind" Anton Kolonin, Mike Ross, Cate Hartley, Karin Verspoor and the tragically prematurely deceased Jeff Pressing (compared to whom we are all mental midgets), who all made seri
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
rkable, ambitious, peculiar AGI-oriented firm existed. Special shout-outs to the "Voice of Reason" Pei Wang and the "Siberian Madmind" Anton Kolonin, Mike Ross, Cate Hartley, Karin Verspoor and the tragically prematurely deceased Jeff Pressing (compared to whom we are all mental midgets), who all made seriou
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
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