(17th-March-2020)
The knowledge base required for online computation can be built initially at design time and then augmented offline by the agent.
An ontology is a specification of the meaning of the symbols used in an information system. It specifies what is being modeled and the vocabulary used in the system. In the simplest case, if the agent is using explicit state-based representation with full observability, the ontology specifies the mapping between the world and the state. Without this mapping, the agent may know it is in, say, state 57, but, without the ontology, this information is just a meaningless number to another agent or person. In other cases, the ontology defines the features or the individuals and relationships.
There are three major roles of Off-line involved with a knowledge-based system:
Software engineers build the inference engine and user interface. They typically know nothing about the contents of the knowledge base. They need not be experts in the use of the system they implement; however, they must be experts in the use of a programming language like Java, Lisp, or Prolog rather than in the knowledge representation language of the system they are designing.
Domain experts are the people who have the appropriate prior knowledge about the domain. They know about the domain, but typically they know nothing about the particular case that may be under consideration. For example, a medical domain expert would know about diseases, symptoms, and how they interact but would not know the symptoms or the diseases of the particular patient. A delivery robot domain expert may know the sort of individuals that must be recognized, what the battery meter measures, and the costs associated with various actions. Domain experts typically do not know the particulars of the environment the agent would encounter - for example, the details of the patient for the diagnostic assistant or the details of the room a robot is in.
Knowledge engineers design, build, and debug the knowledge base in consultation with domain experts. They know about the details of the system and about the domain through the domain expert. They know nothing about any particular case. They should know about useful inference techniques and how the complete system works.
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