Knowledge-Rich Environments and Prodigy
Architectures
Knowledge-Rich Environments and Prodigy
Architectures
In the
domains in which Prodigy has been applied, there
may be much more knowledge that can be learned than would actually be useful
(i.e., the domains are combinatorially explosive).
This lead to the strategy of
deliberative learning as exemplified
by the
utility metric for the evaluation
of learned control rules via
Explanation-Based Learning.
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