Adaptive critic methods have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, nonlinear and nonstationary environments. In this study, a novel probabilistic dual heuristic programming (DHP) based adaptive critic controller is proposed...

Most Prolog implementations are based on backward chaining techniques. However, there are many applications in which forward chaining ones are desirable such as in dynamic programming. In this paper, we first introduce a variant of a Prolog interpreter that computes interpolations and then introduce the notion of sequential queries. These two notions allow a combination of both forms of reasoni...

Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. ‎‎Standard DEA models are ‎‎quite limited models‎, ‎in the sense that they do not consider a DMU ‎‎at different times‎. ‎To resolve this problem‎, ‎DEA models with dynamic ‎‎structures have been proposed‎.‎In a recent pape...

Optimizing highway alignments is a very complex engineering problem. None of existing methods has totally solved the problem In this paper we build an optimization model for highway 3D alignment based on two-stage dynamic programming, in which the comprehensive cost and design constraints are embedded. In the first stage: we formulate the optimization of alignment as a network problem by establ...

one major branch in mathematical sciences, which recently has been given especial attention, is optimization, including various methods such as linear programming, integer programming, and dynamic programming. due to the unique characteristics of air treatment systems, specifically multistage nature of such systems, dynamic programming has been widely applied. the purpose of this paper is to fi...