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