Learning in Meta-Reasoning Architectures
Learning in Meta-Reasoning Architectures
MAX can
learn
when the rules and primitive operators needed for learning are
included in the architecture and then invoked.
The architecture explicitly facilitates learning by
providing a
homogeneous
representation of
knowledge and a
declarative storage of knowledge.
Logic frames
can nest knowledge such
that changes, including additions and deletions of logic, can be performed
in a syntactically homogeneous manner.
Learning in MAX involves
self-modification
to the architecture.
Return to the Issues Index for this Architecture.
Return to the top of this architecture.
Go to a Discussion of this
issue for multiple architectures.
Current Location: Meta-Reasoning-Issues-Learning