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22.12 Coals and Time 81 22.12 Goals and Time The CogPrime system maintains an explicit list of "Ubergoals", which as will be explained in Chapter 24, receive attentional currency which they may then allocat
hema execution in the first place. The problem of credit assignment thus becomes a problem of creating appropriate heuristics to guide inference of ImplicationLinks of the form described above. Assignment of credit is then implicit in the calculation of truth values for these links. The difficulty is that the pr
cedure Learning as Program Learning 30.1 Introduction Broadly speaking, the learning of predicates and schemata (executable procedures) is done in CogPrime via a number of different methods, including for example PLN inference and concept predicatization (to be discussed in later chapters). Most of thes
resent is carried out, either by - PLN inference within OpenCog, drawing the conclusion that a block is present from the exported predicates, using ImplicationLinks comprising a working definition of a "block" - A predicate comprising the definition of "block", previously imported into DeSTIN from OpenCog and
49.6 Cognitive Processes 481 CogPrime's multi-memory design, it's natural to consider CogPrime's cognitive processes in terms of which memory subsystems they focus on (although, this is
ergoals like gaining knowledge are not funded as much with STI currency just now, as they are not immediately relevant. Action selection, based on ImplicationLinks derived via PLN (between various possible activ- ities and the subgoal S) causes it to start experimentally building some blocks structures. Past ex
concepts in one of Douglas HoEstadter's books. Naturally, real concept heterarchies are far more large, complex and tangled than even this one. In CogPrime, ECAN enforces heterarchy via building SymmetricHebbianLinks, and PLN by building SimilarityLinks, IntensionalSimilarityLinks and ExtensionalSimilar
or of Link2Atom. However, the ideas embodied in these rules may be useful; if cleaned 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
n concepts in one of Douglas Hofstadter’s books. Naturally, real concept heterarchies are far more large, complex and tangled than even this one. In CogPrime, ECAN enforces heterarchy via building SymmetricHebbianLinks, and PLN by building SimilarityLinks, IntensionalSimilarityLinks and ExtensionalSimilari
intelligent system explicitly represents in its knowledge base, and expends some resources trying to achieve. Goal Nodes (which may be Nodes or, e.g. ImplicationLinks) are used for this purpose in OpenCog. e Goal-Driven Learning: Learning that is driven by the cognitive schematic i.e. by the quest of figuring out
Entities connected to both CogPrime and ImplicationLinks
OpenCog
ORGANIZATION
Marc Rich
PERSONDeSTIN
ORGANIZATIONConceptNodes
ORGANIZATIONMindAgents
PERSON
George W. Bush
PERSON
Stephen Hawking
PERSON
Joscha Bach
PERSONPredicateNode
LOCATION
Marvin Minsky
PERSONPredicateNodes
ORGANIZATIONNil Geisweiller
PERSONTruthValues
ORGANIZATIONArtificial General Intelligence
ORGANIZATIONCassio Pennachin
PERSON
Joel Pitt
PERSONSTICurrency
LOCATIONthe Webmind AI Engine
ORGANIZATIONHebbian Learning
ORGANIZATION
Dorner
ORGANIZATION