Progress in artificial intelligence

Progress in artificial intelligence

Artificial intelligence can be evaluated on constrained and well-defined problems that allow comparison with human performance. Such tests have been termed subject matter expert Turing tests. Smaller problems provide more achievable goals and there are an ever-increasing number of positive results.

Performance evaluation

The broad classes of outcome for an AI test are:
* optimal: it is not possible to perform better
* strong super-human: performs better than all humans
* super-human: performs better than most humans
* sub-human: performs worse than most humans

Optimal

* Checkers [cite web | url=http://www.sciencemag.org/cgi/content/abstract/1144079 | title=Checkers Is Solved | date=2007-07-19 | accessdate=2007-07-20 | publisher=Science | first=Jonathan | last=Schaeffer]

uper-human

* Backgammon: strong super-human [cite journal |last=Tesauro |first=Gerald |url=http://www.research.ibm.com/massive/tdl.html |title=Temporal difference learning and TD-Gammon |journal=Communications of the ACM |volume=38 |issue=3 |month=March |year=1995 |pages=58–68 |doi=10.1145/203330.203343]
* Bridge: nearing strong super-human [Computer bridge#Computers versus humans]
* Chess: nearing strong super-human [Computer Chess#Computers versus humans]
* Reversi: strong super-human [Reversi#Computer_opponents]
* Scrabble: strong super-human [doi|10.1016/S0004-3702(01)00166-7]

ub-human

* Go [Computer Go#Computers versus humans]
* Machine translation
* Most everyday tasks performed by humans.

ee also

*Technology development

References


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