Epstein Secrets

N nodes are activated and exported to the OpenCog Atomspace • Recognition that a block is present 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"

ning to bridge DeSTIN and PLN Ls intended to fit. This architecture is not yet fully implemented, but is a straightforward extension of the current OpenCog architecture for processing data from game worlds IGEA08], and is scheduled for implementation later in 2013 in the course of a funded project invo

(tv4) ANDLink tv5 = OF2(tvi, tv2, tv3, tv4) Near (self , toy) (tits) The target theorem is "How near I am to the toy if I climb on the pillow." PredictivelmplicationLink Climb_on(pillow) Near(self, toy) (?) And the inference chain as follows 1. Axiom 2 with axiom 1 Near(toy, cupboard_edge) (tv6) 2. Step 1 with a

us to attractor neural nets. The OpenCog design also contains a mechanism called Psynese (not yet implemented), in- tended to make it easier for one OpenCog instance to translate its personal thoughts into the mental language of another OpenCog instance. This translation process may be quite subtle, sin

representation, with an explicit (uncertain) logical aspect as well as an explicit subsymbolic aspect more analogous to attractor neural nets. The OpenCog design also contains a mechanism called Psynese (not yet implemented), in- tended to make it easier for one OpenCog instance to translate its persona

$imultaneousANDLink which combine logical relation between the argument with temporal relation between their arguments. For instance, we might say PredictivelmplicationLink PredicateNode: JumpOffCliff PredicateNode: Dead or including arguments, PredictivelmplicationLink EvaluationLink JumpOffCliff $X EvaluationLink

us to attractor neural nets. The OpenCog design also contains a mechanism called Psynese (not yet implemented), in- tended to make it easier for one OpenCog instance to translate its personal thoughts into the mental language of another OpenCog instance. This translation process may be quite subtle, since

d representation, with an explicit (uncertain) logical aspect as well as an explicit subsymbolic aspect more analogous to attractor neural nets. The OpenCog design also contains a mechanism called Psynese (not yet implemented), in- tended to make it easier for one OpenCog instance to translate its persona

indicates the likelihood of the sequence of events occurring in that order, with gap lying within the specified time interval. The truth value of the PredictivelmplicationLink version indicates the likelihood of the second event, conditional on the occurrence of the first event (within the given time interval restriction).