Hi Liz,

Yes, this is quite exciting, more so than Watson or Deep Blue because it
tries to be more generic.
The latest wave of excitement seems to come from Google's Deep Mind. Here's
a paper about it, with some videos you can see even without paying:

http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html

Reinforcement learning is an old idea. Every time we see the qualifier
"deep" in something AI-related these days, it seems to mean that some old
idea is finally living to its potential through the availability of immense
computational power and data sources. There are more subtleties, of course,
but they seem to be mostly a matter of some parameterization secret-sauce.
Also, exploring large parameterization spaces is also something that
becomes more feasible with more computational power.

Cheers,
Telmo.

On Tue, Mar 31, 2015 at 11:36 PM, LizR <[email protected]> wrote:

> I hadn't come across this before. Another step towards AIhood...
>
> General game players are computer systems able to play strategy games
>> based solely on formal game descriptions supplied at "runtime".  (In other
>> words, they don't know the rules until the game starts.)  Unlike
>> specialized game players, such as Deep Blue, general game players cannot
>> rely on algorithms designed in advance for specific games; they must
>> discover such algorithms themselves.  General game playing expertise
>> depends on intelligence on the part of the game player and not just
>> intelligence of the programmer of the game player.
>
>
> www.coursera.org/course/ggp
>
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