scholarly journals A Neural Network-Based Policy Iteration Algorithm with Global $$H^2$$-Superlinear Convergence for Stochastic Games on Domains

2020 ◽  
Author(s):  
Kazufumi Ito ◽  
Christoph Reisinger ◽  
Yufei Zhang
Keyword(s):  
Neural Network ◽  
Superlinear Convergence ◽  
Stochastic Games ◽  
Policy Iteration ◽  
Iteration Algorithm ◽  
Policy Iteration Algorithm

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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