Computer architecture for training a correlithm object processing system

A correlithm object processing system training method, comprising:

• receiving, by a trainer engine, a real world input value and a real world output value;
• sending, by the trainer engine, a node entry request to a node engine in response to receiving the real world input value and the real world output value, wherein the node entry request triggers the node engine to generate an entry in a node table that identifies:
• a plurality of source correlithm objects, wherein each source correlithm object is a point in an n-dimensional space represented by a binary string;
• and
• a plurality of target correlithm objects, wherein:
• each target correlithm object is a point in the n-dimensional space represented by a binary string, and
• each target correlithm object is linked with a source correlithm object from among the plurality of source correlithm objects;
• receiving, by the trainer engine, a source correlithm object and a target correlithm object in response to sending the node entry request;
• sending, by the trainer engine, the real world input value and the source correlithm object to a sensor engine;
• generating, by the sensor engine, an entry in a sensor table linking the real world input value and the source correlithm object in response to receiving the real world input value and the source correlithm object;
• sending, by the trainer engine, the real world output value and the target correlithm object to an actor engine;
• and
• generating, by the actor engine, an entry in an actor table linking the real world output value and the target correlithm object in response to receiving the real world output value and the target correlithm object.

A computer program product comprising executable instructions stored in a non-transitory computer readable medium such that when executed by a processor causes the processor to emulate a trainer in a correlithm object processing system configured to:

• receive a real world input value and a real world output value;
• send a node entry request to a node engine in response to receiving the real world input value and the real world output value, wherein the node entry request triggers the node engine to generate an entry in a node table that identifies:
• a plurality of source correlithm objects, wherein each source correlithm object is a point in an n-dimensional space represented by a binary string;
• and
• a plurality of target correlithm objects, wherein:
• each target correlithm object is a point in the n-dimensional space represented by a binary string, and
• each target correlithm object is linked with a source correlithm object from among the plurality of source correlithm objects;
• receive a source correlithm object and a target correlithm object in response to sending the node entry request;
• send the real world input value and the source correlithm object to a sensor engine, wherein sending the real world input value and the source correlithm object to the sensor engine triggers the sensor engine to generate an entry in a sensor table linking the real world input value and the source correlithm object;
• send the real world output value and the target correlithm object to an actor engine, wherein sending the real world output value and the target correlithm object to the actor engine triggers the actor engine to generate an entry in an actor table linking the real world output value and the target correlithm object.