Knowledge-based problem-solving comprises two processes, modellingand programming. Current AI languages and environments support only the programming process. Next generation languages and environments will have to support the intellectuallychallenging modelling component in the first place. On the road toward knowledge level modeling environments able to assist the full range of modelling activities involved in problem-solving, the first goal to be achieved is the design of a language for representing problem solving models at the knowledge level. This paper describes MODEL, an enhanced term classification language in the KLONE family which extends classification technology to allow the description of the domain, inference, task and strategic levels knowledge based problem-solving models are composed of. The paper gives a detailed account of the language and illustrates it with an encompassing analysis of the problem-solving and knowledge acquisition components of SALT, a well-known generic problem-solving model for constructive tasks.
knowledge acquisition, knowledge modelling, term classification languages, generic problem-solving models, knowledge processing mechanisms, ontological analysis, KADS.
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