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Quote: raytrace said: Please provide me with an objective test that proves AI is (or will be) there, and I will take back my statement.
Ok... Let's take the answers.com definition:
artificial intelligence n. (Abbr. AI) The ability of a computer or other machine to perform those activities that are normally thought to require intelligence. The branch of computer science concerned with the development of machines having this ability.
Chess is normally thought to require intelligence, a computer or machine can play chess, this means artificial intelligence exists.
The subjective part here is what is "normally thought" and "intelligence". We have to give definitions to those to make it more objective, but we will end up in a definition discussion while we probably both know what we try to say.
Nothing is pure objective, but AI does exist for me with my definition. It's a logic result of the definitions I give to AI and intelligence.
The fun in philosophy, for me, is not in looking if something exists according to what definitions, but to think about the subject itself.
You might have a different definition of AI, please let me know what your definition is!
Quote: In this paper, a roving eye neural network is evolved to solve this problem. The network has a small input field that can scan boards of any size. Experiments demonstrate that (1) The same roving eye architecture can play on different board sizes, and (2) experience gained by playing on a small board provides an advantage for further learning on a larger board.
The experimental results show that a TWEANN that has learned to play Go on a 5x5 board will learn how to play on a 7x7 board significantly faster than a TWEANN that starts out learning on a 7x7 board. From the standpoint of a TWEANN, the two board sizes represent entirely different, but related games.
In the authors own words:
Quote: Conclusion: The roving eye architecture is an appealing approach to Go because it is the same for any board size. It is also powerful because it can turn to face different directions, allowing it to process symmetrical configurations with the same connections. When compared with evolving from scratch, a 7x7 eye pre-evolved in a 5x5 board achieved significantly faster learning, and significantly higher final fitness. This result establishes that (1) The roving eye can indeed play on different board sizes, and (2) the roving eye aids incremental evolution on increasingly large boards. Thus, the roving eye is a potentially important component of learning systems that aim to perform well on larger boards even when learning directly on such large boards is prohibitively complex.
-------------------- Just another spore in the wind.
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