Download or read book Representing Plans Under Uncertainty written by Peter F. Haddawy and published by . This book was released on 1991 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: The language can represent the chance that facts hold and events occur at various times. It can represent the chance that actions and other events affect the future. The model of action distinguishes between action feasibility, executability, and effects. Using this distinction, a notion of expected utility for acts that may not be feasible is defined. This notion is used to reason about the chance that trying a plan will achieve a given goal. An algorithm for the problem of building construction planning is developed and the logic is used to prove the algorithm correct."
Download or read book Representing Plans Under Uncertainty written by Peter Haddawy and published by Springer. This book was released on 1994 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This monograph integrates AI and decision-theoretic approaches to the representation of planning problems by developing a first-order logic of time, chance, and action for representing and reasoning about plans. The semantics of the logic incorporates intuitive properties of time, chance, and action central to the planning problem. The logical language integrates both modal and probabilistic constructs and allows quantification over time points, probability values, and domain individuals. The language can represent the chance that facts hold and events occur at various times and that actions and other events affect the future. An algorithm for the problem of building construction planning is developed and the logic is used to prove the algorithm correct."--PUBLISHER'S WEBSITE.
Download or read book Representing Plans Under Uncertainty written by Peter Haddawy and published by . This book was released on 2014-09-01 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Uncertainty in Artificial Intelligence written by MKP and published by Elsevier. This book was released on 2014-06-28 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty Proceedings 1994
Download or read book Defense Resource Planning Under Uncertainty written by Robert J. Lempert and published by Rand Corporation. This book was released on 2016-01-29 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Defense planning faces significant uncertainties. This report applies robust decision making (RDM) to the air-delivered munitions mix challenge. RDM is quantitative, decision support methodology designed to inform decisions under conditions of deep uncertainty and complexity. This proof-of-concept demonstration suggests that RDM could help defense planners make plans more robust to a wide range of hard-to-predict futures.
Download or read book Handbook on Cities and Complexity written by Portugali, Juval and published by Edward Elgar Publishing. This book was released on 2021-09-16 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by some of the founders of complexity theory and complexity theories of cities (CTC), this Handbook expertly guides the reader through over forty years of intertwined developments: the emergence of general theories of complex self-organized systems and the consequent emergence of CTC.
Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Download or read book Uncertainty in Artificial Intelligence written by David Heckerman and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Artificial Intelligence contains the proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence held at the Catholic University of America in Washington, DC, on July 9-11, 1993. The papers focus on methods of reasoning and decision making under uncertainty as applied to problems in artificial intelligence (AI) and cover topics ranging from knowledge acquisition and automated model construction to learning, planning, temporal reasoning, and machine vision. Comprised of 66 chapters, this book begins with a discussion on causality in Bayesian belief networks before turning to a decision theoretic account of conditional ought statements that rectifies glaring deficiencies in classical deontic logic and forms a sound basis for qualitative decision theory. Subsequent chapters explore trade-offs in constructing and evaluating temporal influence diagrams; normative engineering risk management systems; additive belief-network models; and sensitivity analysis for probability assessments in Bayesian networks. Automated model construction and learning as well as algorithms for inference and decision making are also considered. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.
Download or read book Principles of Knowledge Representation and Reasoning written by Bernhard Nebel and published by Morgan Kaufmann Publishers. This book was released on 1992 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stringently reviewed papers presented at the October 1992 meeting held in Cambridge, Mass., address such topics as nonmonotonic logic; taxonomic logic; specialized algorithms for temporal, spatial, and numerical reasoning; and knowledge representation issues in planning, diagnosis, and natural langu
Download or read book Algorithmic Foundations of Robotics XII written by Ken Goldberg and published by Springer Nature. This book was released on 2020-05-06 with total page 931 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the outcomes of the 12th International Workshop on the Algorithmic Foundations of Robotics (WAFR 2016). WAFR is a prestigious, single-track, biennial international meeting devoted to recent advances in algorithmic problems in robotics. Robot algorithms are an important building block of robotic systems and are used to process inputs from users and sensors, perceive and build models of the environment, plan low-level motions and high-level tasks, control robotic actuators, and coordinate actions across multiple systems. However, developing and analyzing these algorithms raises complex challenges, both theoretical and practical. Advances in the algorithmic foundations of robotics have applications to manufacturing, medicine, distributed robotics, human–robot interaction, intelligent prosthetics, computer animation, computational biology, and many other areas. The 2016 edition of WAFR went back to its roots and was held in San Francisco, California – the city where the very first WAFR was held in 1994. Organized by Pieter Abbeel, Kostas Bekris, Ken Goldberg, and Lauren Miller, WAFR 2016 featured keynote talks by John Canny on “A Guided Tour of Computer Vision, Robotics, Algebra, and HCI,” Erik Demaine on “Replicators, Transformers, and Robot Swarms: Science Fiction through Geometric Algorithms,” Dan Halperin on “From Piano Movers to Piano Printers: Computing and Using Minkowski Sums,” and by Lydia Kavraki on “20 Years of Sampling Robot Motion.” Furthermore, it included an Open Problems Session organized by Ron Alterovitz, Florian Pokorny, and Jur van den Berg. There were 58 paper presentations during the three-day event. The organizers would like to thank the authors for their work and contributions, the reviewers for ensuring the high quality of the meeting, the WAFR Steering Committee led by Nancy Amato as well as WAFR’s fiscal sponsor, the International Federation of Robotics Research (IFRR), led by Oussama Khatib and Henrik Christensen. WAFR 2016 was an enjoyable and memorable event.
Download or read book Handbook of Temporal Reasoning in Artificial Intelligence written by Michael David Fisher and published by Elsevier. This book was released on 2005-03-01 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection represents the primary reference work for researchers and students in the area of Temporal Reasoning in Artificial Intelligence. Temporal reasoning has a vital role to play in many areas, particularly Artificial Intelligence. Yet, until now, there has been no single volume collecting together the breadth of work in this area. This collection brings together the leading researchers in a range of relevant areas and provides an coherent description of the breadth of activity concerning temporal reasoning in the filed of Artificial Intelligence. Key Features: - Broad range: foundations; techniques and applications - Leading researchers around the world have written the chapters - Covers many vital applications - Source book for Artificial Intelligence, temporal reasoning - Approaches provide foundation for many future software systems · Broad range: foundations; techniques and applications · Leading researchers around the world have written the chapters · Covers many vital applications · Source book for Artificial Intelligence, temporal reasoning · Approaches provide foundation for many future software systems
Download or read book Flexibility and Real Estate Valuation under Uncertainty written by David Geltner and published by John Wiley & Sons. This book was released on 2018-02-19 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a revolutionary conceptual framework and practical tools to quantify uncertainty and recognize the value of flexibility in real estate development This book takes a practical "engineering" approach to the valuation of options and flexibility in real estate. It presents simple simulation models built in universal spreadsheet software such as Microsoft Excel®. These realistically reflect the varying and erratic sources of uncertainty and price dynamics that uniquely characterize real estate. The text covers new analytic procedures that are valuable for existing properties and enable a new, more profitable perspective on the planning, design, operation, and evaluation of large-scale, multi-phase development projects. The book thereby aims to significantly improve valuation and investment decision making. Flexibility and Real Estate Valuation under Uncertainty: A Practical Guide for Developers is presented at 3 levels. First, it introduces and explains the concepts underlying the approach at a basic level accessible to non-technical and non-specialized readers. Its introductory and concluding chapters present the important “big picture” implications of the analysis for economics and valuation and for project design and investment decision making. At a second level, the book presents a framework, a roadmap for the prospective analyst. It describes the practical tools in detail, taking care to go through the elements of the approach step-by-step for clarity and easy reference. The third level includes more technical details and specific models. An Appendix discusses the technical details of real estate price dynamics. Associated web pages provide electronic spreadsheet templates for the models used as examples in the book. Some features of the book include: • Concepts and tools that are simple and accessible to a broad audience of practitioners; • An approach relevant for all development projects; • Complementarity with the author's Commercial Real Estate Analysis & Investments—the most-cited real estate investments textbook on the market. Flexibility and Real Estate Valuation under Uncertainty: A Practical Guide for Developers is for everyone studying or concerned with the implementation of large-scale or multi-phase real estate development projects, as well as property investment and valuation more generally.
Download or read book Fusion Methodologies in Crisis Management written by Galina Rogova and published by Springer. This book was released on 2016-01-21 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book emphasizes a contemporary view on the role of higher level fusion in designing crisis management systems, and provide the formal foundations, architecture and implementation strategies required for building dynamic current and future situational pictures, challenges of, and the state of the art computational approaches to designing such processes. This book integrates recent advances in decision theory with those in fusion methodology to define an end-to-end framework for decision support in crisis management. The text discusses modern fusion and decision support methods for dealing with heterogeneous and often unreliable, low fidelity, contradictory, and redundant data and information, as well as rare, unknown, unconventional or even unimaginable critical situations. Also the book examines the role of context in situation management, cognitive aspects of decision making and situation management, approaches to domain representation, visualization, as well as the role and exploitation of the social media. The editors include examples and case studies from the field of disaster management.
Download or read book Inductive Logic Programming written by Stephen Muggleton and published by Springer Science & Business Media. This book was released on 2007-07-27 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the 16th International Conference on Inductive Logic Programming, ILP 2006, held in Santiago de Compostela, Spain, in August 2006. The papers address all current topics in inductive logic programming, ranging from theoretical and methodological issues to advanced applications.
Download or read book Logic Programming written by Danny De Schreye and published by MIT Press. This book was released on 1999-11-08 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes tutorials, lectures, and refereed papers on all aspects of logic programming, including theoretical foundations, constraints, concurrency and parallelism, deductive databases, language design and implementation, nonmonotonic reasoning, and logic programming and the Internet. The International Conference on Logic Programming, sponsored by the Association for Logic Programming, includes tutorials, lectures, and refereed papers on all aspects of logic programming, including theoretical foundations, constraints, concurrency and parallelism, deductive databases, language design and implementation, nonmonotonic reasoning, and logic programming and the Internet.
Download or read book Strategic Power Plant Investment Planning Under Fuel and Carbon Price Uncertainty written by Ansgar Geiger and published by KIT Scientific Publishing. This book was released on 2014-08-20 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The profitability of power plant investments depends strongly on uncertain fuel and carbon prices. In this doctoral thesis, we combine fundamental electricity market models with stochastic dynamic programming to evaluate power plant investments under uncertainty. The application of interpolation-based stochastic dynamic programming and approximate dynamic programming allows us to consider a greater variety of stochastic fuel and carbon price scenarios compared to other approaches.
Download or read book Decision Making Process written by Denis Bouyssou and published by John Wiley & Sons. This book was released on 2013-05-10 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the main methods and results in the formal study of the human decision-making process, as defined in a relatively wide sense. A key aim of the approach contained here is to try to break down barriers between various disciplines encompassed by this field, including psychology, economics and computer science. All these approaches have contributed to progress in this very important and much-studied topic in the past, but none have proved sufficient so far to define a complete understanding of the highly complex processes and outcomes. This book provides the reader with state-of-the-art coverage of the field, essentially forming a roadmap to the field of decision analysis. The first part of the book is devoted to basic concepts and techniques for representing and solving decision problems, ranging from operational research to artificial intelligence. Later chapters provide an extensive overview of the decision-making process under conditions of risk and uncertainty. Finally, there are chapters covering various approaches to multi-criteria decision-making. Each chapter is written by experts in the topic concerned, and contains an extensive bibliography for further reading and reference.