Constructing Adequate Mental Models
DOI:
https://doi.org/10.51408/1963-0018Keywords:
Mental models, Regularization, Adequate, Constructive, Explaining, Human-computer interactions, Neuron netsAbstract
Mental systems represent realities, have varying effectiveness with respect to our goals and are processed to support utilization and gain benefits from utilities.
Classifiers induced by mental systems are effective with respect to the goals insofar as regularly provide utilities and enhance effectiveness of modeling of those utilities constructively and adequately.
In the paper we discuss ontological, constructive and systemic models of mental systems, mentals, comparable by expressiveness with algorithms and natural languages, provide arguments of their adequacy for explaining, understanding and human-computer interactions as well as convince to follow the ideas of inventors of algorithms in adequate modeling of mental behavior.
To consist functional and connectivity mental models and recalling that artificial neuron nets are systems of classifiers, we provide evidence that mentals can be reduced to systems of classifiers as well.
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