‎a novel technique for solving the uncertainty under the environment of neutrosophic theory of choice

‎when it comes to solving dynamic‎ ‎programming challenges‎, ‎it is essential to have a well-structured ‎‎‎‎decision theory‎. ‎as a result‎, ‎the decision-makers must operate in a‎ ‎dynamically complicated environment where appropriate and rapid‎ ‎reaction in a cooperative way is the fundamental key to effectively‎ ‎completing the task‎. ‎we express a theory of decision modeling and‎ ‎axiomatizing a decision-making process‎. ‎the payoffs and‎ ‎probabilities are represented with simplified neutrosophic sets‎. ‎we‎ ‎therefore‎, ‎provide the theory of choice with the implementation of‎ ‎simplified neutrosophic sets‎. ‎by exploiting the idea of pure‎ ‎strategy‎, ‎we introduce two steps‎: ‎in the first step‎, ‎for each‎ ‎attractive point‎, ‎some particular event is selected that can bring‎ ‎about a relatively neutrosophic upper payoff with a relatively‎ ‎neutrosophic upper probability or a relatively neutrosophic lower‎ ‎payoff with a relatively neutrosophic upper probability‎. ‎a‎ ‎decision-maker selects the most favored attractive point in the‎ ‎second stage‎, ‎based on the focus on all attractive points‎. ‎neutrosophic focus theory has been introduced to improve overall‎ ‎performance with more flexibility in complex decision-making‎. ‎the‎ ‎approach suggested in this work has been implemented in a real-life‎ ‎example to determine its effectiveness‎. ‎the proposed method is shown to‎ ‎be the most useful for ranking scenarios and addressing dynamic‎ ‎programming problems in decision-making‎.