Reward distribution routine prioritizes sub goals by updating
their desirability attributes.
Reward distribution routine distributes reward
value among the concepts responsible for the goal satisfaction.
One of super goals is (partially) satisfied. The super goal calculates reward and passes it to reward distribution routine. Reward distribution routine distributes
reward among cause concepts responsible for the super goal satisfaction.
1) Reward value.
2)
Specified super goal.
Every super
goal is represented by at least one concept in the main memory.
This “super
goal’s deputy concept” has: ConceptId = SuperGoalConceptId
Step #1:
Find cause concepts responsible for the super goal satisfaction
That means
to select all records from cause-effect
relation table with EffectConceptID = SuperGoalConceptId:
SELECT
CauseConceptID,
Coherence
FROM CauseEffectRelation
WHERE EffectConceptID = SuperGoalConceptId
Step #2:
Distribute reward among selected concepts proportionally Coherence
attribute.
That means
to update desirability attribute of
every selected concept.
Strong AI
knows about cause and effect of everything (including causes for super goal
satisfaction) from learning, in particular from experiment.