6.5 Goal-Oriented Dynamics in CogPrime 113 example, perhaps MOSES would discover that older males wearing ties tend not to become regular visitors. If the new playmate is an older male wearing a tie, this is directly applicable. But if the current playmate is wearing a tuxedo, then PLN may be helpful via reasoning that even though a tuxedo is not a tie, it’s a similar form of fancy dress — so PLN may extend the MOSES-learned rule to the present case and infer that the new playmate is not likely to be a regular visitor. 6.5 Goal-Oriented Dynamics in CogPrime CogPrime’s dynamics has both goal-oriented and “spontaneous” aspects; here for simplicity’s sake we will focus on the goal-oriented ones. The basic goal-oriented dynamic of the CogPrime system, within which the various types of memory are utilized, is driven by implications known as “cognitive schematics”, which take the form Context \ Procedure > Goal < p> (summarized C A P > G). Semi-formally, this implication may be interpreted to mean: “If the context C' appears to hold currently, then if I enact the procedure P, I can expect to achieve the goal G with certainty p.” Cognitive synergy means that the learning processes corresponding to the different types of memory actively cooperate in figuring out what procedures will achieve the system’s goals in the relevant contexts within its environment. CogPrime’s cognitive schematic is significantly similar to production rules in classical ar- chitectures like SOAR and ACT-R (as reviewed in Chapter 4; however, there are significant differences which are important to CogPrime’s functionality. Unlike with classical production rules systems, uncertainty is core to CogPrime’s knowledge representation, and each CogPrime cognitive schematic is labeled with an uncertain truth value, which is critical to its utilization by CogPrime’s cognitive processes. Also, in CogPrime, cognitive schematics may be incomplete, missing one or two of the terms, which may then be filled in by