13.3 Atoms: Their Types and Weights 255
For instance, there are Atom types referring to general natural language data types, such as
WordNode SentenceNode WordInstanceNode DocumentNode
plus more specific ones referring to relationships that are part of link-grammar parses of sen- tences
FeatureNode
FeatureLink LinkGrammarRelationshipNode LinkGrammarDisjunctNode
or RelEx semantic interpretations of sentences
e DefinedLinguisticConceptNode e DefinedLinguisticRelationshipNode e PrepositionalRelationshipNode
There are also Atom types corresponding to entities important for embodying OpenCog in a virtual world, e.g.
ObjectNode AvatarNode HumanoidNode UnknownObjectNode AccessoryNode
13.3.8 Truth Values and Attention Values
CogPrime Atoms (Nodes and Links) are quantified with truth values that, in their simplest form, have two components, one representing probability (strength) and the other representing weight of evidence; and also with attention values that have two components, short-term and long-term importance, representing the estimated value of the Atom on immediate and long- term time-scales.
In practice many Atoms are labeled with CompositeTruthValues rather than elementary ones. A composite truth value contains many component truth values, representing truth values of the Atom in different contexts and according to different estimators.
It is important to note that the CogPrime declarative knowledge representation is neither a neural net nor a semantic net, though it does have some commonalities with each of these traditional representations. It is not a neural net because it has no activation values, and involves no attempts at low-level brain modeling. However, attention values are very loosely analogous to time-averages of neural net activations. On the other hand, it is not a semantic net because of the broad scope of the Atoms in the network: for example, Atoms may represent percepts, procedures, or parts of concepts. Most CogPrime Atoms have no corresponding English label. However, most CogPrime
Atoms do have probabilistic truth values, allowing logical semantics.
HOUSE_OVERSIGHT_013171