Metacontrol of a Traffic Simulator Using Situation Semantics
In the present article, we present how concepts from Situation Semantics (, ) can be used for the metacontrol tasks of a traffic simulator. Situation Semantics, as presented in , is one of the most ambitious theories for knowledge representation, especially for representing the meaning of natural language. The theory can also be used in current AI systems to represent the knowledge of a variety of domains. We show how concepts from Situation Semantics can be used for the metacontrol tasks of a traffic simulator. We address not only formal aspects of a situational theory for our traffic domain, but also present a representation language by means of which different traffic situations can be represented.
KeywordsRepresentation Language Location Constraint Traffic Situation Traffic Simulator Argument Position
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