Self - observation Principle for Estimating the Other ’ s Internal State – New Computational Theory of Communication –

We propose a computational theory of internal-state estimation for others, which is the basis of information processing in human communication. To estimate internal states of the other equivalent to the self, we have to deal with two substantial difficulties, restriction of the estimator’s parameter dimension and conversion between objective and subjective information. The proposed computational theory that solves both difficulties is based on self-observation principle. Learning the dynamics of the self provides prior knowledge of the dynamics of the other, which reduces the restriction of the parameter dimension; learning the association between the subjective state for the self and the objective observation of the self provides a mechanism for conversion between objective observation of the other and subjective information to the other. In this paper, we formalize communication in a framework of dynamics-estimation problems, and describe the two difficulties and our proposal on the framework. We also discuss relations of our proposal to evolutional psychology and neuroscience.