A Class of Self-Interacting Processes with Applications to Games and Reinforced Random Walks

IF 2.4 2区 数学 Q2 AUTOMATION & CONTROL SYSTEMS SIAM Journal on Control and Optimization Pub Date : 2010-06-01 DOI:10.1137/080721091
M. Benaïm, Olivier Raimond
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引用次数: 9

Abstract

This paper studies a class of non-Markovian and nonhomogeneous stochastic processes on a finite state space. Relying on a recent paper by Benaim, Hofbauer, and Sorin [SIAM J. Control Optim., 44 (2005), pp. 328-348] it is shown that, under certain assumptions, the asymptotic behavior of occupation measures can be described in terms of a certain set-valued deterministic dynamical system. This provides a unified approach to simulated annealing type processes and permits the study of new models of vertex reinforced random walks and new models of learning in games such as Markovian fictitious play.
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一类自交互过程及其在游戏和强化随机漫步中的应用
研究有限状态空间上的一类非马尔可夫非齐次随机过程。根据Benaim, Hofbauer和Sorin最近的一篇论文[SIAM J. Control Optim.][j], 44 (2005), pp. 328-348]表明,在一定的假设下,职业测度的渐近行为可以用一定的集值确定性动力系统来描述。这为模拟退火过程提供了一种统一的方法,并允许研究顶点强化随机漫步的新模型和马尔可夫虚拟游戏等游戏中的新学习模型。
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来源期刊
CiteScore
4.00
自引率
4.50%
发文量
143
审稿时长
12 months
期刊介绍: SIAM Journal on Control and Optimization (SICON) publishes original research articles on the mathematics and applications of control theory and certain parts of optimization theory. Papers considered for publication must be significant at both the mathematical level and the level of applications or potential applications. Papers containing mostly routine mathematics or those with no discernible connection to control and systems theory or optimization will not be considered for publication. From time to time, the journal will also publish authoritative surveys of important subject areas in control theory and optimization whose level of maturity permits a clear and unified exposition. The broad areas mentioned above are intended to encompass a wide range of mathematical techniques and scientific, engineering, economic, and industrial applications. These include stochastic and deterministic methods in control, estimation, and identification of systems; modeling and realization of complex control systems; the numerical analysis and related computational methodology of control processes and allied issues; and the development of mathematical theories and techniques that give new insights into old problems or provide the basis for further progress in control theory and optimization. Within the field of optimization, the journal focuses on the parts that are relevant to dynamic and control systems. Contributions to numerical methodology are also welcome in accordance with these aims, especially as related to large-scale problems and decomposition as well as to fundamental questions of convergence and approximation.
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