Non-monotonic Learning
An agent that may learn knowledge that contradicts what it already knows
is said to learn non-monotonically.
So it may replace old knowledge with new if it believes there is sufficient
reason to do so.
The advantages of non-monotonic learning are:
- Increased applicability to
real domains,
- Greater freedom in the order things are learned in
Architectures that are constrained to add only knowledge consistent
with what has already been learned
are said to learn monotonically.
Architectures having this agent property include:
Go to the List of Common Agent Properties.
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