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e of the Cognitive Science Society. 2004. CB00. W. H. Calvin and D. Bickerton. Lingua er Machin. MIT
. Springer-Verlag, 2005. HB06. Jeff Hawkins and Sandra Blakeslee. On Intelligence. Brown Walker, 2006. HDY+12. Geoffrey Hinton, Li Deng, bong Yu, George bald, Abdel rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, and Tara Sainathand Brian Kingsbury. Deep neural netw
r the latter are learned via MOSES or via some other means. The textual realization of Combo resembles LISP with less syntactic sugar. Internally a Combo program is represented as a program tree. • Composer: In the PLN design, a rule is denoted a composer if it needs premises for generating its conse
ve its fingers to pick up a cup, coordinating its movements with its visual perceptions. It's certainly possible to represent this sort of thing in Combo, but Combo may be an awkward tool. However, if one represents low-level procedures like this using another method, e.g. learned cell assemblies in a
the question of programs in what programming language, and in this context we have made a fairly traditional choice, using a special language called Combo that is essentially a minor variant of LISP, and supplying Combo with a set of customized primitives intended to reduce the length of the typical p
Body. Harvard University Press, 1962. BW88. R. W. Byrne and A. Whiten. Machiavellian Intelligence.
r the latter are learned via MOSES or via some other means. The textual realization of Combo resembles LISP with less syntactic sugar. Internally a Combo program is represented as a program tree. • Composer: In the PLN design, a rule is denoted a composer if it needs premises for generating its conse
p the rules might profitably be ported into the Atomspace as ImplicationLinks. • Representation Building: A stage within MOSES, wherein a candidate Combo program tree (within a deme) is modified by replacing one or more tree nodes with alternative tree nodes, thus obtaining a new, different candidate
e created. Using frequent itemset mining to find temporal motif maps is a similar, but slightly more complex process. Here, one fixes a time-window W. Then, for each activation cycle index t, one creates a set S(t) consisting of pairs of the form: (A, a) where A is an Atom and 0 ≤ s ≤ W is an int
uesses produced by pure procedure learning methods), it may still be valuable to have this procedure in compact and rapidly executable form such as Combo provides. To proceed with the technical description of predicate schematization in CogPrime. we first need the notion of an "executable predicate".
tand: all else equal, a predicate embodied in a small Combo tree is better than a predicate embodied in a big one. There is some work hidden here in Combo tree reduction; ideally, one would like to find the smallest representation of a given Combo tree, but this is a computationally formidable problem
of the Body. Harvard University Press, 1962. R. W. Byrne and A. Whiten. Machiavellian Intelligence.
d up the rules might profitably be ported into the Atomspace as ImplicationLinks. Representation Building: A stage within MOSES, wherein a candidate Combo program tree (within a deme) is modified by replacing one or more tree nodes with alternative tree nodes, thus obtaining a new, different candidate p
her the latter are learned via MOSES or via some other means. The textual realization of Combo resembles LISP with less syntactic sugar. Internally a Combo program is represented as a program tree. e Composer: In the PLN design, a rule is denoted a composer if it needs premises for generating its conseq
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