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This work suggests the estimation method developed in relation to theposition of the robotic system (RS) operator, showing his degree of riskproneness. The base models are: Hurwitz pessimism/optimism criterion anddecision trees. The problem is solved using the reverse setting: we estimatepessimism/optimism parameter of the operator (decision taker) by observing whatdecisions he makes when controlling the RS. The solution context of suchdecision taker position estimation problems can be: using RS in emergencysituations, in military actions and other situations connected with theuncertainty of the situation.

Risk Proneness Estimation Method Developed in Relation to the Decision Taker that Controls the Robotic System