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Re: Artificial Intelligence Programming in Perl

by Abigail-II (Bishop)
on Jul 01, 2002 at 14:01 UTC ( [id://178554]=note: print w/replies, xml ) Need Help??


in reply to Re: Re: Artificial Intelligence Programming in Perl
in thread Artificial Intelligence Programming in Perl

Declared dead by who?
The academic world? The Computing Science community? In the 80s and the 90s, AI was defocussed on. It of course never disappeared, but it certainly wasn't as prominent as in the late 70s and early 80s.
What were they referring to by AI?
Eh, "Artificial Intelligence"? ;-) Making complex decisions as fast and in a similar way as humans can?

I just read through the paper you referred to, and it looks a bit bullshit to me. P and NP problems are defined for Turing machines, quantum machines are a fundamentally different class of machines. There are other machines possible where it hardly makes sense to talk about P and NP (take for instance an oracle and each time your algorithm has to guess, you ask the oracle instead).

I do however have serious doubts about the feasability of quantum computers. Perhaps when the NSA starts decrypting 4096 bit GPG messages almost instantly I'll become a believer.

Abigail

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Re: Re: Artificial Intelligence Programming in Perl
by demerphq (Chancellor) on Jul 01, 2002 at 16:44 UTC
    Generally I agree with this and your other post. AI has all the hallmarks of a degenerate research programme. But I did want to raise one point... ;-)

    Eh, "Artificial Intelligence"? ;-) Making complex decisions as fast and in a similar way as humans can?

    This combines what I would consider the two primary objectives of AI in a way that makes them sound like one.

    1. AI as an investigative tool for a plausable model of cognition. Much work was invested into AI as a method to explain how we think we think. This research tended to be very domain specific and scaled poorly. It also had fundamental philosophical problems that put to lie many of the grandisoe claims that were made by it.
    2. AI as an approach to solve problems that computers are typically bad at and humans are typically good at. This was a slighly more fruitful avenue. Usually the models bore little if any relationship to how we think we think. Examples of this are the AL work done in emergent phenomenon, GA's, neural networks.
    The former appears to be almost totally abandonded. (Although high quality chess programs are perhaps one of its successes.) The latter is being used in a small number of unlikely areas with considerable success. (Chip design is a notable example)

    Yves / DeMerphq
    ---
    Writing a good benchmark isnt as easy as it might look.

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