Theoretical and Pragmatic Basis of Our Context Modeling

A model has predictive power that a representation does not because it is limited to observation smoothing. The model can be expressed in different representation formalisms, with more or less expressiveness, although each formalism has strengths, weaknesses and limits. This chapter describes the concepts of activity, mental model and mental representation in Cognitive Sciences in light of the Contextual-Graphs (CxG) formalism for contextual reasoning and conversely, the contribution of the mental-model concept to the CxG formalism. It briefly presents several real-world applications over a period of 25 years in a very large spectrum of domains. The chapter presents the origins of the proposed scientific approach for context-based modeling of an activity in AI, starting from the approach developed in biology, which is illustrated by a previous work on the modeling of the calcium metabolism.