For anything whose function and sequencing we thoroughly understand the programming is straightforward and easy, at least in the conceptual sense. That covers most games, including video games. The computer’s “side” in a video game, for example, which looks conceptually difficult, most of the time turns out logically to be only decision trees.
The challenge is the tasks we can’t precisely define, like general intelligence. The rewarding approach here is to break down processes into identifiable subtasks. A case in point is understanding natural languages, one of whose essential questions is, “What is the meaning of “meaning?” In terms of a machine it can only be the content of a subroutine or pointers to subroutines. The input problem, converting sentences into sets of executable concepts, is thus approachable. The output problem, however, converting unpredictable concepts into words, is much tougher. It may involve growing decision trees on the fly.
For anything whose function and sequencing we thoroughly understand the programming is straightforward and easy, at least in the conceptual sense. That covers most games, including video games. The computer’s “side” in a video game, for example, which looks conceptually difficult, most of the time turns out logically to be only decision trees.
The challenge is the tasks we can’t precisely define, like general intelligence. The rewarding approach here is to break down processes into identifiable subtasks. A case in point is understanding natural languages, one of whose essential questions is, “What is the meaning of “meaning?” In terms of a machine it can only be the content of a subroutine or pointers to subroutines. The input problem, converting sentences into sets of executable concepts, is thus approachable. The output problem, however, converting unpredictable concepts into words, is much tougher. It may involve growing decision trees on the fly.