Epstein Secrets

emory to interact intimately, in a way that allows them to help each other squelch combinatorial explosions. This hypothesis lies at the core of the CogPrime Artificial General Intelligence design, an integrative cognitive architecture that is partially implemented in the current OpenCog software system.

ntend our virtual parrot to do. A high level depiction of some of the learning that would be expected to occur in this case is given in Diagram 2. Program Learning (MOSES) Learns procedure to "get food from a difficult spot using a Wier Sends procedure to PLN for further learning. The action "pick up stick" w

emory to interact intimately, in a way that allows them to help each other squelch combinatorial explosions. This hypothesis lies at the core of the CogPrime Artificial General Intelligence design, an integrative cognitive architecture that is partially implemented in the current OpenCog software system.

ntend our virtual parrot to do. A high level depiction of some of the learning that would be expected to occur in this case is given in Diagram 2. Program Learning (MOSES) Learns procedure to "get food from a difficult spot using a stick" Sends procedure to PLN for further learning. The action "pick up stick-

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

vations regarding the implications of this choice for procedure learning, and the formal representation of procedure learning with CogPrime. 30.1.1 Program Learning An optimization problem may be defined as follows: a solution space S is specified, together with some fitness function on solutions, where "solvin