Abstract

The paper gives general definitions of the mathematical theory of emotional robots able to forget older information. A formalized concept of relative receptivity of the robot to education is introduced. An algorithm of a voice training program for public speakers described in the paper is based on the theory of emotional robots. Also the paper presents a method of estimation of a coefficient of human emotional memory and estimation of a relative receptivity of a robot and a human to education; the method is based on application of the voice training program.

Highlights

  • According to forecasts, by 2018 the world market of humanoid robots has to make 25.5 billion dollars

  • Assume the robot’s emotion has a form of a certain integrated function Mi (τ ) where τ is the current time of emotional effect, τ ∈[0,T ], T is the step i.e. the time step which is the duration of emotion, i is the serial number of an emotion experienced by the robot

  • Analyzing (11) we can conclude that θ j and θ i+ j can be neglected at large values of i and j, and the relative receptivity can be estimated as α ≈ θ k

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Summary

Introduction

According to forecasts, by 2018 the world market of humanoid robots has to make 25.5 billion dollars.

Methods
Results
Conclusions

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