This work suggests the estimation method developed in relation to the position of the robotic system (RS) operator, showing his degree of risk proneness. The base models are: Hurwitz pessimism/optimism criterion and decision trees. The problem is solved using the reverse setting: we estimate pessimism/optimism parameter of the operator (decision taker) by observing what decisions he makes when controlling the RS. The solution context of such decision taker position estimation problems can be: using RS in emergency situations, in military actions and other situations connected with the uncertainty of the situation.
@article{arxiv.1703.06161,
title = {Risk Proneness Estimation Method Developed in Relation to the Decision Taker that Controls the Robotic System},
author = {Valery Vilisov},
journal= {arXiv preprint arXiv:1703.06161},
year = {2017}
}