Epstein Secrets

s implicit in the state transition graphs of the mind and world should be inter-mappable via a high- probability morphism. • Mind OS: A synonym for the OpenCog Core. • MindAgent: An OpenCog software object, residing in the CogServer, that carries out some processes in interaction with the Atomspace. A given con

to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where "reward" may mean simply the Truth Value of some Atom defined as "reward"). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which

s implicit in the state transition graphs of the mind and world should be inter-mappable via a high- probability morphism. • Mind OS: A synonym for the OpenCog Core. • MindAgent: An OpenCog software object, residing in the C-ogServer, that carries out some processes in interaction with the Atomspace. A given co

to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where "reward" may mean simply the Truth Value of some Atom defined as "reward"). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which

es implicit in the state transition graphs of the mind and world should be inter-mappable via a high- probability morphism. e Mind OS: A synonym for the OpenCog Core. e MindAgent: An OpenCog software object, residing in the CogServer, that carries out some processes in interaction with the Atomspace. A given con

to learn procedures that will maxi- mize some Goal whose Truth Value is estimated via an expected reward calculation (where *reward” may mean simply the Truth Value of some Atom defined as ”reward”). Goal-driven learning is more general than reinforcement learning as thus defined; and the learning that CogPrime does, which is