Epstein Secrets

s, or observe the consequences of various hypothetical situations. Particularly important for dealing with episodic knowledge. • Interval Algebra: Allen Interval Algebra, a mathematical theory of the relationships be- tween time intervals. CogPrime utilizes a fuzzified version of classic Interval Algebra. • IRC Learn

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, or observe the consequences of various hypothetical situations. Particularly important for dealing with episodic knowledge. • Interval Algebra: Allen Interval Algebra, a mathematical theory of the relationships be- tween time intervals. CogPrime utilizes a fuzzified version of classic Interval Algebra. • IRC Learn

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

ces, or observe the consequences of various hypothetical situations. Particularly important for dealing with episodic knowledge. e Interval Algebra: Allen Interval Algebra, a mathematical theory of the relationships be- tween time intervals. CogPrime utilizes a fuzzified version of classic Interval Algebra. e IRC Learn

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