Searching for “Counter Text” as a Way to Solve the Problem

Abstract

Problem solving is an example of purposeful behavior that boils down to searching for a description of a chain of situations that lead to a target situation from the current situation in internal or external sources, or to synthesize such a chain if it is not found in the annals. To do this, we need to find a (counter) text, the semantic network of which includes both the current situation and the target situation (and so that these two situations are related to each other in the semantic network of this text), and then the semantic network of this (counter) text bridges (closes the “gap” between) the two original situations—the current situation and the target one, thereby offering the solution to the original problem. Algorithmically searching for counter text comes down to the formation of semantic networks of candidate texts, which contain chains of nodes, including nodes that in the subsequent projection onto the hippocampal situation models, and then onto the anterior cortex, can be considered as those establishing the connection between the current and target situations. For using the TextAnalyst technology, we can solve the problem of constructing a homogeneous directed weighted semantic network where the desired chain can be found.