Complete Knowledge

Sometimes an agent knows all possibly relevant information about its domain. In this case, learning is not required for domain understanding and the behavior of the system can be precoded, dependent on perceptions.

Associated with these environments is the closed world assumption, under which any fact not known to the agent can be taken to be false. This is similar to complete world knowledge, in that the agent knows everything that is true about its domain. This assumption greatly simplifies declarative representation tasks.

Vere and Bickmore have suggested the (informal) 99% rule which relaxes the requirement for complete domain knowledge. In specifying parameter ranges for objects Homer may encounter in the course of its activities, they limit the range from the space of all possibilities to ranges which cover 99% of the possible cases. The presumption is that if the agent is correct 99% of the time, it will be performing acceptably and the outlying ranges can simply be ignored.

Architectures requiring some measure of complete knowledge include:


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