In this paper, we study a model that mimics the programming operation of memory cells. This was first introduced by Lastras-Montano et al. for continuous-alphabet channels, and later Bunte Lapidoth discrete memoryless channels (DMC). Under paradigm assume cells are programmed sequentially indiv...

Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments These algorithms including the TD algo rithm of Sutton and the Q learning algorithm of Watkins can be motivated heuristically as approximations to dynamic program ming DP In this paper we provide a rigorous proof of convergence of these DP ba...

the partial differential equations for water flow and solute transport in a two-dimensional saturated domain are rendered discrete using the finite difference technique; the resulting system of algebraic equations is solved using a dynamic programming (dp) method. the advantage of the dp algorithm is that the problem is converted from solving an algebraic system of order nc(nl-1) nc(nl-1) into...

We present a new Lagrangian-based iterative technique for rate{distortion optimization under multiple rate constraints. We show how for sets of \lin-ear" constraints this technique can be proven to be optimal up to a convex hull approximation. As an application we consider the problem of optimal buuer-constrained bit allocation. Our technique can be used to nd an excellent approximation to the ...

In this paper, we revisit the problem of query optimization in relational DBMS. We propose a scheme to reduce the search space of Dynamic Programming based on reuse of query plans among similar subqueries. The method generates the cover set of similar subgraphs present in the query graph and allows their corresponding subqueries to share query plans among themselves in the search space. Numerou...

the control problem and dynamic programming is a powerful tool in economics and management. we review the dynamic programming problem from its beginning up to its present stages. a problem which was involved in physics and mathematics in i 7” century led to a branch of mathematics called calculus of variation which was used in economic, and management at the end of the first quarter of the 20” ...

Practical exploitation of optimal dual control (ODC) theory continues to be hindered by the difficulties involved in numerically solving the associated stochastic dynamic programming (SDPs) problems. In particular, high-dimensional hyper-states coupled with the nesting of optimizations and integrations within these SDP problems render their exact numerical solution computationally prohibitive. ...

This paper presenting case studies in modern large scale constrained optimization, the purpose of which is to illustrate how recent advances in algorithms and modelling languages have made it easy to solve difficult optimization problems using of software. In this paper we use measure theory technique and iterative dynamic programming algorithm for solving of a trajectory optimization problem: ...