𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Saddle-point calculation for constrained finite Markov chains

✍ Scribed by E. Gómez-Ramı́rez; K. Najim; A.S. Poznyak

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
275 KB
Volume
27
Category
Article
ISSN
0165-1889

No coin nor oath required. For personal study only.

✦ Synopsis

This paper considers a zero-sum constrained stochastic game. The control objective of each participant is to optimize his limiting average payo . In this case, the behavior of each player is modelled with a ÿnite ergodic controlled Markov chain. The saddle point is shown to be the stationary strategy representing the solutions of two related Linear Programming Problems given in duality form. Several numerical examples illustrate the e ectiveness of this suggested approach. In one of them, a single product market model is presented explaining the behavior of the game in a real situation.

📜 SIMILAR VOLUMES

Penalty function and adaptive control of
Penalty function and adaptive control of constrained finite Markov chains
✍ K. Najim; A. S. Poznyak 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 161 KB 👁 2 views

In this paper we consider the adaptive control of constrained finite ergodic controller Markov chains whose transition probabilities are unknown. The control policy is designed to achieve the minimization of a loss function under a set of inequality constraints. The average values of conditional mat

Bayesian analysis for finite Markov chai
Bayesian analysis for finite Markov chains
✍ B.R.Bhat M.N.; Badade 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 143 KB

Bayesian approach to inference for Markov chains (MC) has many advantages over classical approach. This paper discusses how tests for one-sided and two-sided hypotheses involving two or more parameters of ÿnite Markov chains can be carried out. The posterior probabilities (Pvalues), Bayes factors, h