Download or read book An Experimental Study of Decisions in Dynamic Optimization Problems written by Charles Noussair and published by . This book was released on 1998 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Management and Intelligent Decision Making in Complex Systems An Optimization Driven Approach written by Ameer Hamza Khan and published by Springer Nature. This book was released on 2020-10-29 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the authors focus on three aspects related to the development of articulated agents: presenting an overview of high-level control algorithms for intelligent decision-making of articulated agents, experimental study of the properties of soft agents as the end-effector of articulated agents, and accurate management of low-level torque-control loop to accurately control the articulated agents. This book summarizes recent advances related to articulated agents. The motive behind the book is to trigger theoretical and practical research studies related to articulated agents.
Download or read book The Handbook of Experimental Economics written by John H. Kagel and published by Princeton University Press. This book was released on 2016-09-20 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt: An indispensable survey of new developments and results in experimental economics When The Handbook of Experimental Economics first came out in 1995, the notion of economists conducting lab experiments to generate data was relatively new. Since then, the field has exploded. This second volume of the Handbook covers some of the most exciting new growth areas in experimental economics, presents the latest results and experimental methods, and identifies promising new directions for future research. Featuring contributions by leading practitioners, the Handbook describes experiments in macroeconomics, charitable giving, neuroeconomics, other-regarding preferences, market design, political economy, subject population effects, gender effects, auctions, and learning and the economics of small decisions. Contributors focus on key developments and report on experiments, highlighting the dialogue between experimenters and theorists. While most of the experiments consist of laboratory studies, the book also includes several chapters that report extensively on field experiments related to the subject area studied. Covers exciting new growth areas in experimental economics Features contributions by leading experts Describes experiments in macroeconomics, charitable giving, neuroeconomics, market design, political economy, gender effects, auctions, and more Highlights the dialogue by experimenters with theorists and each other Includes several chapters covering field experiments related to the subject area studied
Download or read book Dynamic Optimization in the Age of Big Data written by Bradley Eli Sturt and published by . This book was released on 2020 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis revisits a fundamental class of dynamic optimization problems introduced by Dantzig (1955). These decision problems remain widely studied in many applications domains (e.g., inventory management, finance, energy planning) but require access to probability distributions that are rarely known in practice. First, we propose a new data-driven approach for addressing multi-stage stochastic linear optimization problems with unknown probability distributions. The approach consists of solving a robust optimization problem that is constructed from sample paths of the underlying stochastic process. As more sample paths are obtained, we prove that the optimal cost of the robust problem converges to that of the underlying stochastic problem. To the best of our knowledge, this is the first data-driven approach for multi-stage stochastic linear optimization problems which is asymptotically optimal when uncertainty is arbitrarily correlated across time. Next, we develop approximation algorithms for the proposed data-driven approach by extending techniques from the field of robust optimization. In particular, we present a simple approximation algorithm, based on overlapping linear decision rules, which can be reformulated as a tractable linear optimization problem with size that scales linearly in the number of data points. For two-stage problems, we show the approximation algorithm is also asymptotically optimal, meaning that the optimal cost of the approximation algorithm converges to that of the underlying stochastic problem as the number of data points tends to infinity. Finally, we extend the proposed data-driven approach to address multi-stage stochastic linear optimization problems with side information. The approach combines predictive machine learning methods (such as K-nearest neighbors, kernel regression, and random forests) with the proposed robust optimization framework. We prove that this machine learning-based approach is asymptotically optimal, and demonstrate the value of the proposed methodology in numerical experiments in the context of inventory management, scheduling, and finance.
Download or read book The New Palgrave Dictionary of Economics written by and published by Springer. This book was released on 2016-05-18 with total page 7493 pages. Available in PDF, EPUB and Kindle. Book excerpt: The award-winning The New Palgrave Dictionary of Economics, 2nd edition is now available as a dynamic online resource. Consisting of over 1,900 articles written by leading figures in the field including Nobel prize winners, this is the definitive scholarly reference work for a new generation of economists. Regularly updated! This product is a subscription based product.
Download or read book Optimization and Decision Science written by Raffaele Cerulli and published by Springer Nature. This book was released on 2022-01-03 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects selected contributions from the international conference “Optimization and Decision Science” (ODS2020), which was held online on November 19, 2020, and organized by AIRO, the Italian Operations Research Society. The book offers new and original contributions on optimization, decisions science and prescriptive analytics from both a methodological and applied perspective, using models and methods based on continuous and discrete optimization, graph theory and network optimization, analytics, multiple criteria decision making, heuristics, metaheuristics, and exact methods. In addition to more theoretical contributions, the book chapters describe models and methods for addressing a wide diversity of real-world applications, spanning health, transportation, logistics, public sector, manufacturing, and emergency management. Although the book is aimed primarily at researchers and PhD students in the Operations Research community, the interdisciplinary content makes it interesting for practitioners facing complex decision-making problems in the afore-mentioned areas, as well as for scholars and researchers from other disciplines, including artificial intelligence, computer sciences, economics, mathematics, and engineering.
Download or read book Paper written by and published by . This book was released on 1998 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Behavioural and Experimental Economics written by Steven Durlauf and published by Springer. This book was released on 2016-04-30 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
Download or read book Economic Psychology and Experimental Economics written by Simon Kemp and published by Routledge. This book was released on 2013-08-21 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last ten years have seen an enormous surge of interest in issues that are common to psychology and economics. How do people make decisions about economic issues? How should they make such decisions? Does public policy or regulation succeed in its aim of helping people make these decisions? What situations aid cooperation? This volume explores some of the ways in which economists and psychologists have tried to answer these questions. The authors are an international mix of economists and psychologists, and as such they demonstrate a diverse range of approaches to tackling different aspects of these issues. This is a frontier area for both psychology and economics, and consequently it is relatively free, lawless and, above all, exciting. This collection reflects the diversity and energy that characterise this rapidly growing interdisciplinary field. This book was originally published as a special issue of New Zealand Economic Papers.
Download or read book Neural Approximations for Optimal Control and Decision written by Riccardo Zoppoli and published by Springer Nature. This book was released on 2019-12-17 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc. Features of the text include: • a general functional optimization framework; • thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems; • comparison of classical and neural-network based methods of approximate solution; • bounds to the errors of approximate solutions; • solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with one decision maker or several; • applications of current interest: routing in communications networks, traffic control, water resource management, etc.; and • numerous, numerically detailed examples. The authors’ diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.
Download or read book The Neuroscience and Psychophysiology of Experience Based Decisions written by Eldad Yechiam and published by Frontiers E-books. This book was released on with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: In experience-based decisions people learn to make decisions by sampling the relevant alternatives and getting feedback. The study of experience-based decisions has recently revealed some robust regularities that differ from how people make decisions based on descriptions. For example, people were found to underweight small probability events in experience-based decisions, while overweighting them in decisions based on descriptions (i.e. where the participants have full information about the outcome distributions but no feedback). This is now commonly referred to as the description-experience gap. In parallel to the recent advancement in Decision Science, neuroscientists have for a long while used the experience-based decisions paradigm for analyzing brain-behavior interactions. For example, phenomena such as the feedback-based Error-Related Negativity (fERN) in event-related potentials and the role of non-declarative knowledge in selecting advantageously were discovered using experience-based tasks. The goal of the current Research Topic is to combine two sources of knowledge concerning experience-based decisions: State of the art models in decision science, and neuroscientific and psychophysiological approaches that shed light on the working of the brain in these decisions. Also relevant are process-based analyses of fractions of behavior in these types of decisions. We consider original empirical work and theoretical analyses of existing datasets.
Download or read book Decision Trees with Hypotheses written by Mohammad Azad and published by Springer Nature. This book was released on 2022-11-18 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the concept of a hypothesis about the values of all attributes is added to the standard decision tree model, considered, in particular, in test theory and rough set theory. This extension allows us to use the analog of equivalence queries from exact learning and explore decision trees that are based on various combinations of attributes, hypotheses, and proper hypotheses (analog of proper equivalence queries). The two main goals of this book are (i) to provide tools for the experimental and theoretical study of decision trees with hypotheses and (ii) to compare these decision trees with conventional decision trees that use only queries, each based on a single attribute. Both experimental and theoretical results show that decision trees with hypotheses can have less complexity than conventional decision trees. These results open up some prospects for using decision trees with hypotheses as a means of knowledge representation and algorithms for computing Boolean functions. The obtained theoretical results and tools for studying decision trees with hypotheses are useful for researchers using decision trees and rules in data analysis. This book can also be used as the basis for graduate courses.
Download or read book Undergraduate Catalog written by University of Michigan--Dearborn and published by . This book was released on 2013 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Approximate Dynamic Programming written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2007-10-05 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.
Download or read book Intelligent Scheduling of Robotic Flexible Assembly Cells written by Khalid Karam Abd and published by Springer. This book was released on 2015-11-08 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the design of Robotic Flexible Assembly Cell (RFAC) with multi-robots. Its main contribution consists of a new effective strategy for scheduling RFAC in a multi-product assembly environment, in which dynamic status and multi-objective optimization problems occur. The developed strategy, which is based on a combination of advanced solution approaches such as simulation, fuzzy logic, system modeling and the Taguchi optimization method, fills an important knowledge gap in the current literature and paves the way for future research towards the goal of employing flexible assembly systems as effectively as possible despite the complexity of their scheduling.
Download or read book Wonderful Solutions and Habitual Domains for Challenging Problems in Changeable Spaces written by Moussa Larbani and published by Springer. This book was released on 2016-08-24 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a new paradigm called ‘Optimization in Changeable Spaces’ (OCS) as a useful tool for decision making and problem solving. It illustrates how OCS incorporates, searches, and constructively restructures the parameters, tangible and intangible, involved in the process of decision making. The book elaborates on OCS problems that can be modeled and solved effectively by using the concepts of competence set analysis, Habitual Domain (HD) and the mental operators called the 7-8-9 principles of deep knowledge of HD. In addition, new concepts of covering and discovering processes are proposed and formulated as mathematical tools to solve OCS problems. The book also includes reformulations of a number of illustrative real-life challenging problems that cannot be solved by traditional optimization techniques into OCS problems, and details how they can be addressed. Beyond that, it also includes perspectives related to innovation dynamics, management, artificial intelligence, artificial and e-economics, scientific discovery and knowledge extraction. This book will be of interest to managers of businesses and institutions, policy makers, and educators and students of decision making and behavior in DBA and/or MBA.
