Analysis of Markov Chain Models of Adaptive Processes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Analysis of Markov Chain Models of Adaptive Processes write by K. R. Kaplan. This book was released on 1965. Analysis of Markov Chain Models of Adaptive Processes available in PDF, EPUB and Kindle. Learning and adaptation are considered to be stochastic in nature by most modern psychologists and by many engineers. Markov chains are among the simplest and best understood models of stochastic processes and, in recent years, have frequently found application as models of adaptive processes. A number of new techniques are developed for the analysis of synchronous and asynchronous Markov chains, with emphasis on the problems encountered in the use of these chains as models of adaptive processes. Signal flow analysis yields simplified computations of asymptotic success probabilities, delay times, and other indices of performance. The techniques are illustrated by several examples of adaptive processes. These examples yield further insight into the relations between adaptation and feedback. (Author).
Adaptive Markov Control Processes
Adaptive Markov Control Processes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Adaptive Markov Control Processes write by Onesimo Hernandez-Lerma. This book was released on 2012-12-06. Adaptive Markov Control Processes available in PDF, EPUB and Kindle. This book is concerned with a class of discrete-time stochastic control processes known as controlled Markov processes (CMP's), also known as Markov decision processes or Markov dynamic programs. Starting in the mid-1950swith Richard Bellman, many contributions to CMP's have been made, and applications to engineering, statistics and operations research, among other areas, have also been developed. The purpose of this book is to present some recent developments on the theory of adaptive CMP's, i. e. , CMP's that depend on unknown parameters. Thus at each decision time, the controller or decision-maker must estimate the true parameter values, and then adapt the control actions to the estimated values. We do not intend to describe all aspects of stochastic adaptive control; rather, the selection of material reflects our own research interests. The prerequisite for this book is a knowledgeof real analysis and prob ability theory at the level of, say, Ash (1972) or Royden (1968), but no previous knowledge of control or decision processes is required. The pre sentation, on the other hand, is meant to beself-contained,in the sensethat whenever a result from analysisor probability is used, it is usually stated in full and references are supplied for further discussion, if necessary. Several appendices are provided for this purpose. The material is divided into six chapters. Chapter 1 contains the basic definitions about the stochastic control problems we are interested in; a brief description of some applications is also provided.
Sensitivity Analysis: Matrix Methods in Demography and Ecology
Sensitivity Analysis: Matrix Methods in Demography and Ecology - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sensitivity Analysis: Matrix Methods in Demography and Ecology write by Hal Caswell. This book was released on 2019-04-02. Sensitivity Analysis: Matrix Methods in Demography and Ecology available in PDF, EPUB and Kindle. This open access book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases. Readers will discover results on the sensitivity of statistics of longevity, life disparity, occupancy times, the net reproductive rate, and statistics of Markov chain models in demography. They will also see applications of sensitivity analysis to population growth rates, stable population structures, reproductive value, equilibria under immigration and nonlinearity, and population cycles. Individual stochasticity is a theme throughout, with a focus that goes beyond expected values to include variances in demographic outcomes. The calculations are easily and accurately implemented in matrix-oriented programming languages such as Matlab or R. Sensitivity analysis will help readers create models to predict the effect of future changes, to evaluate policy effects, and to identify possible evolutionary responses to the environment. Complete with many examples of the application, the book will be of interest to researchers and graduate students in human demography and population biology. The material will also appeal to those in mathematical biology and applied mathematics.
Markov Chain Aggregation for Agent-Based Models
Markov Chain Aggregation for Agent-Based Models - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Markov Chain Aggregation for Agent-Based Models write by Sven Banisch. This book was released on 2015-12-21. Markov Chain Aggregation for Agent-Based Models available in PDF, EPUB and Kindle. This self-contained text develops a Markov chain approach that makes the rigorous analysis of a class of microscopic models that specify the dynamics of complex systems at the individual level possible. It presents a general framework of aggregation in agent-based and related computational models, one which makes use of lumpability and information theory in order to link the micro and macro levels of observation. The starting point is a microscopic Markov chain description of the dynamical process in complete correspondence with the dynamical behavior of the agent-based model (ABM), which is obtained by considering the set of all possible agent configurations as the state space of a huge Markov chain. An explicit formal representation of a resulting “micro-chain” including microscopic transition rates is derived for a class of models by using the random mapping representation of a Markov process. The type of probability distribution used to implement the stochastic part of the model, which defines the updating rule and governs the dynamics at a Markovian level, plays a crucial part in the analysis of “voter-like” models used in population genetics, evolutionary game theory and social dynamics. The book demonstrates that the problem of aggregation in ABMs - and the lumpability conditions in particular - can be embedded into a more general framework that employs information theory in order to identify different levels and relevant scales in complex dynamical systems
Markov Chains and Decision Processes for Engineers and Managers
Markov Chains and Decision Processes for Engineers and Managers - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Markov Chains and Decision Processes for Engineers and Managers write by Theodore J. Sheskin. This book was released on 2016-04-19. Markov Chains and Decision Processes for Engineers and Managers available in PDF, EPUB and Kindle. Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and service systems. However, most books on Markov chains or decision processes are often either highly theoretical, with few examples, or highly prescriptive, with little justification for the steps of the algorithms u
