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terarchical graph of the main concepts in one of Douglas HoEstadter's books. Naturally, real concept heter
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
un references. Lingua, 44:311-338, 1978. Hof79. Douglas Holstadter. Codel, Escher, Bach: An Eternal Golde
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
eterarchical graph of the main concepts in one of Douglas Hofstadter’s books. Naturally, real concept heter
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
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