Glass box knowledge representation may be defined as the ability of rules to examine each other. Architectures with this property automatically have meta-knowledge, and therefore may readily support meta-reasoning.
Glass box representation is useful for modular architectures, so that all modules have access to all knowledge. Glass box representation allows the rules and the architecture to share responsibility to examine, activate and rewards other rules. Also, learning (and esp. multi-method learning) are facilitated by glass box representation because learning modules may write.
The advantages of glass box representation are:
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