A non-heuristic model of decision-making based on human perception under time constraints

In this paper, we discuss the problem of time constraints in a decision process from the aspect of human perception, instead of prevailing heuristics. We propose a decision-making model for locating best alternatives in human-machine interaction that involves human perception in evaluation of gains and losses and time tracking. The results of simulation describe that the proposed model provides a contradictory finding to the heuristic approaches for locating best alternatives at half-time, i.e. half the maximal time constraints. The proposed non-heuristic model contributes to soft-computing algorithms as tools for supporting human-machine interaction by introducing reasonable values for locating best alternatives based on human perception into the stopping criteria for managing a decision process, instead of half-time.