@inbook{d4af6675302e4a999c269d5f118ebbbf,
title = "Improving strategies in stochastic games",
abstract = "In a zero-sum limiting average stochastic game, we evaluate a\textbackslash{}nstrategy \π for the maximizing player, player 1, by the reward \φ\textbackslash{}ns(\π) that \π guarantees to him when starting in state s.\textbackslash{}nA strategy \π is called non-improving if\textbackslash{}n\φs(\π)\⩾\φs(\π[h]) for any state s\textbackslash{}nand for any finite history h, where \π[h] is the strategy \π\textbackslash{}nconditional on the history h; otherwise the strategy is called\textbackslash{}nimproving. We investigate the use of improving and non-improving\textbackslash{}nstrategies, and explore the relation between (non-)improvingness and\textbackslash{}n(\ε-) optimality. Improving strategies appear to play a very\textbackslash{}nimportant role for obtaining \ε optimality, while 0-optimal\textbackslash{}nstrategies are always non-improving. Several examples are given to\textbackslash{}nclarify all these issues",
author = "J. Flesch and F. Thuijsman and Vrieze, \{O.J. J\}",
year = "1998",
doi = "10.1109/CDC.1998.757857",
language = "English",
isbn = "0-7803-4394-8",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "IEEE",
pages = "2674--2679",
booktitle = "Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171)",
}