Epstein Secrets

e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con

. • 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

ed to reach a more orthogonal set. A straightfor- ward way to do this is to exploit the reduction to nor

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

e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con

. • 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

e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. CIM-Dynamic: Concr

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