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l Ant Problem 224 33.3.5 Discussion 229 33.3.6 Conclusion 229 33.4 Integrating Feature Selection Into the Learning Process 230 33.4.1 Machine Learning, Feature Selection and AGI 231 33.4.2 Data- and Feature- Focusable Learning Problems 232 33.4.3 Integrating Feature Selection Into Learning 233
entioned: 1. Via preprocessing of perceptual inputs (e.g. the names of NumberNode, CharacterNodes) 2. Via hard-wiring of names for Schemallodes and PredicateNodes corresponding to built-in elementary schema (e.g. +, AND, Say) If an Atom A has a name n in the system, we may write A.name n On the other hand,
ique that does feature selection repeatedly during the MOSES learning process, rather than just doing it initially prior to MOSES learning. 33.4.1 Machine Learning, Feature Selection and AGI The relation between feature selection and machine learning appears an excellent example of the way that, even when the
specification PredicateNode as true as possible). In evolutionary computing lingo, the specification predicate is a fitness function. Searching for PredicateNodes that embody patterns in the AtomSpace as a whole is a spe- cial case of this kind of learning, where the specification PredicateNode embodies a notio
lvin. The Cerebral Code. MIT Press, 1996. Car85. S. Carey. Conceptual Change in Childhood. MIT Press, 1985. Car97. R Caruana. Multitask learning. Machine Learning, 1997. Cas85. R. Case. Intellectual development: Birth to adulthood. Academic Press, 1985. Cas04. N. L. Cassimatis. Grammatical processing using
. • Imitation Learning: Learning via copying what some other agent is observed to do. • Implication: Often refers to an ImplicationLink between two PredicateNodes, indicating an (extensional, intensional or mixed) logical implication. • Implicit Knowledge Representation: Representation of knowledge via having
2006. William Calvin. The Cerebral Code. MIT Press, 1996. S. Carey. Conceptual Change in Childhood. MIT Press, 1985. R Caruana. Multitask learning. Machine Learning, 1997. R. Case. Intellectual development: Birth to adulthood. Academic Press, 1985. N. L. Cassimatis. Grammatical processing using the mechanisms o
er atoms. Grounded- PredicateNodes and GroundedSchemaNodes connect to explicitly represented procedures (sometimes in the Combo language); ungrounded PredicateNodes and SchemaNodes are abstract and, like ConceptNodes, purely characterized by their relationships. Node Probability: Many PLN inference rules rely on
Entities connected to both Machine Learning and PredicateNodes
PredicateNode
LOCATION
Marc Rich
PERSONConceptNodes
ORGANIZATIONMindAgents
PERSONOpenCog
ORGANIZATIONCogPrime
ORGANIZATIONDeSTIN
ORGANIZATIONCombo
LOCATIONTruthValues
ORGANIZATIONImplicationLinks
ORGANIZATION
Marvin Minsky
PERSONScheduler
ORGANIZATION
Python
ORGANIZATIONSTICurrency
LOCATIONthe Webmind AI Engine
ORGANIZATIONPei Wang
PERSONVariableAtoms
ORGANIZATIONSchemallode
PERSON
Woody Allen
PERSON
Joscha Bach
PERSON