scholarly journals An Efficient Policy Iteration Algorithm for Dynamic Programming Equations

2015 ◽  
Vol 37 (1) ◽  
pp. A181-A200 ◽  
Author(s):  
Alessandro Alla ◽  
Maurizio Falcone ◽  
Dante Kalise
Keyword(s):  
Dynamic Programming ◽  
Policy Iteration ◽  
Iteration Algorithm ◽  
Policy Iteration Algorithm ◽  
Dynamic Programming Equations

scholarly journals An Efficient Policy Iteration Algorithm for Dynamic Programming Equations

PAMM ◽  
2013 ◽  
Vol 13 (1) ◽  
pp. 467-468
Author(s):  
Alessandro Alla ◽  
Maurizio Falcone ◽  
Dante Kalise
Keyword(s):  
Dynamic Programming ◽  
Policy Iteration ◽  
Iteration Algorithm ◽  
Policy Iteration Algorithm ◽  
Dynamic Programming Equations

scholarly journals Algorithms of approximate dynamic programming for hydro scheduling

2020 ◽  
Vol 144 ◽  
pp. 01001
Author(s):  
Iram Parvez ◽  
Jianjian Shen
Keyword(s):  
Dynamic Programming ◽  
Approximate Dynamic Programming ◽  
Unit Commitment ◽  
Optimization Problems ◽  
Policy Iteration ◽  
Least Square ◽  
Iteration Algorithm ◽  
Temporal Difference ◽  
Programming Technique ◽  
Policy Iteration Algorithm

In hydro scheduling, unit commitment is a complex sub-problem. This paper proposes a new approximate dynamic programming technique to solve unit commitment. A new method called Least Square Policy Iteration (LSPI) algorithm is introduced which is efficient and faster in convergence. This algorithm takes the properties of widely used algorithm least square temporal difference (LSTD), enhance it further and make it useful for optimization problems. First value function is to find a fixed policy by using least square temporal difference Q (LSTDQ) algorithm which is similar to LSTD, then LSPI is introduced for making the policy iteration algorithm by using the results of LSTDQ. It combines the data efficiency of LSTDQ and policy-search efficiency of policy iteration.

scholarly journals A policy iteration algorithm for nonzero-sum stochastic impulse games

2019 ◽  
Vol 65 ◽  
pp. 27-45
Author(s):  
René Aïd ◽  
Francisco Bernal ◽  
Mohamed Mnif ◽  
Diego Zabaljauregui ◽  
Jorge P. Zubelli
Keyword(s):  
Nash Equilibrium ◽  
Numerical Methods ◽  
Variational Inequalities ◽  
Convergence Analysis ◽  
Policy Iteration ◽  
Iteration Algorithm ◽  
Value Functions ◽  
Numerical Tests ◽  
Wide Range ◽  
Policy Iteration Algorithm

This work presents a novel policy iteration algorithm to tackle nonzero-sum stochastic impulse games arising naturally in many applications. Despite the obvious impact of solving such problems, there are no suitable numerical methods available, to the best of our knowledge. Our method relies on the recently introduced characterisation of the value functions and Nash equilibrium via a system of quasi-variational inequalities. While our algorithm is heuristic and we do not provide a convergence analysis, numerical tests show that it performs convincingly in a wide range of situations, including the only analytically solvable example available in the literature at the time of writing.

scholarly journals Policy Iteration Algorithm for the Control of Oxygenation

2015 ◽  
Vol 48 (20) ◽  
pp. 517-522 ◽  
Author(s):  
Anake Pomprapa ◽  
Milod Mir Wais ◽  
Marian Walter ◽  
Berno J.E. Misgeld ◽  
Steffen Leonhardt
Keyword(s):  
Policy Iteration ◽  
Iteration Algorithm ◽  
Policy Iteration Algorithm
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