Most models of decision-making in neuroscience assume an infinite horizon, which yields an optimal solution that integrates evidence up to a fixed decision threshold; however, under most experimental as well as naturalistic behavioral settings, the decision has to be made before some finite deadline, which is often experienced as a stochastic quantity, either due to variable external constraint...

This paper formulates and discusses a series of sequential decision problems of the following common structure: A decision alternative of multiple attributes-that is, a job, an employee, or an investment alternative-is to be selected within a certain fixed length of time. An unknown number of alternatives are presented sequentially, either deterministically or in a random manner. The decision m...

in this paper, convex semi-infinite programming is converted to an optimal control model of neural networks and the optimal control model is solved by iterative dynamic programming method. in final, numerical examples are provided for illustration of the purposed method.

In this paper, we presented an optimal iterative decision rule for minimizing total cost in designing a sampling plan for machine replacement problem using the approach of dynamic programming and Bayesian inferences. Cost of replacing the machine and cost of defectives produced by machine has been considered in model. Concept of control threshold policy has been applied for decision making. If ...

This paper analyzes a system subject to repairable and non-repairable failures. Non-repairable failures lead to replacement of the system. Repairable failures, first lead to repair but they lead to replacement after a fixed number of repairs. Operating and repair times follow phase type distributions (PH-distributions) and the pattern of the operating times is modelled by a geometric process. I...

Sequential decision-making tasks are commonplace in our everyday lives. We report the results of an experiment in which human subjects were trained to perform a perceptual matching task, an instance of a sequential decision-making task. We use two benchmarks to evaluate the quality of subjects’ learning. One benchmark is based on optimal performance as defined by a dynamic programming procedure...

In this study, a new warranty service strategy is proposed and analyzed. This strategy adds the renewing free-replacement warranty to a non-repairable product sold under the rebate warranty policy. According to the renewing free-replacement warranty, the seller (manufacturer) is responsible for replacing all failed product during the warranty period, and the warranty begins anew with each repla...

The purpose of this paper is to propose a solu tion methodology for a missile defense problem involving the sequential allocation of defensive resources over a series of engagements The problem is cast as a dynamic program ming Markovian decision problem which is computation ally intractable by exact methods because of its large num ber of states and its complex modeling issues We have em ploye...

| The purpose of this paper is to propose a solution methodology for a missile defense problem involving the sequential allocation of defensive resources over a series of engagements. The problem is cast as a dynamic program-ming/Markovian decision problem, which is computation-ally intractable by exact methods because of its large number of states and its complex modeling issues. We have emplo...

For products sold with a warranty, preventive maintenance (PM) actions by either the manufacturer and/or the buyer has an impact on the total cost for both parties. In this investigation, we use a model to study the effect of PM carried out by the buyer on non-repairable items sold under a free replacement renewing warranty, and a penalty will be incurred by the buyer if the item fails before t...