Understanding in Incomplete Worlds
Most real world domains differ from the micro-worlds traditionally used in A.I. in that they have an incomplete factual database which changes over time. Understanding in these domains can be thought of as the generation of plausible inferences which are able to use the facts available, and res...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/6297 |