Author: Peter F. Haddawy
Publisher:
ISBN:
Category : Knowledge representation (Information theory)
Languages : en
Pages : 350
Book Description
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."
Representing Plans Under Uncertainty
Author: Peter F. Haddawy
Publisher:
ISBN:
Category : Knowledge representation (Information theory)
Languages : en
Pages : 350
Book Description
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."
Publisher:
ISBN:
Category : Knowledge representation (Information theory)
Languages : en
Pages : 350
Book Description
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."
Uncertainty in Artificial Intelligence
Author: MKP
Publisher: Elsevier
ISBN: 1483298604
Category : Computers
Languages : en
Pages : 625
Book Description
Uncertainty Proceedings 1994
Publisher: Elsevier
ISBN: 1483298604
Category : Computers
Languages : en
Pages : 625
Book Description
Uncertainty Proceedings 1994
Defense Resource Planning Under Uncertainty
Author: Robert J. Lempert
Publisher: Rand Corporation
ISBN: 0833093037
Category : History
Languages : en
Pages : 108
Book Description
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.
Publisher: Rand Corporation
ISBN: 0833093037
Category : History
Languages : en
Pages : 108
Book Description
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.
Handbook on Cities and Complexity
Author: Portugali, Juval
Publisher: Edward Elgar Publishing
ISBN: 1789900123
Category : Social Science
Languages : en
Pages : 456
Book Description
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.
Publisher: Edward Elgar Publishing
ISBN: 1789900123
Category : Social Science
Languages : en
Pages : 456
Book Description
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.
Uncertainty in Artificial Intelligence
Author: David Heckerman
Publisher: Morgan Kaufmann
ISBN: 1483214516
Category : Computers
Languages : en
Pages : 554
Book Description
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.
Publisher: Morgan Kaufmann
ISBN: 1483214516
Category : Computers
Languages : en
Pages : 554
Book Description
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.
Principles of Knowledge Representation and Reasoning
Author: Bernhard Nebel
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 834
Book Description
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
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 834
Book Description
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
Decision Making Under Uncertainty
Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262331713
Category : Computers
Languages : en
Pages : 350
Book Description
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.
Publisher: MIT Press
ISBN: 0262331713
Category : Computers
Languages : en
Pages : 350
Book Description
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.
Handbook of Temporal Reasoning in Artificial Intelligence
Author: Michael David Fisher
Publisher: Elsevier
ISBN: 0080533361
Category : Computers
Languages : en
Pages : 753
Book Description
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
Publisher: Elsevier
ISBN: 0080533361
Category : Computers
Languages : en
Pages : 753
Book Description
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
Inductive Logic Programming
Author: Stephen Muggleton
Publisher: Springer Science & Business Media
ISBN: 3540738460
Category : Computers
Languages : en
Pages : 466
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 3540738460
Category : Computers
Languages : en
Pages : 466
Book Description
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.
Flexibility and Real Estate Valuation under Uncertainty
Author: David Geltner
Publisher: John Wiley & Sons
ISBN: 1119106451
Category : Business & Economics
Languages : en
Pages : 258
Book Description
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.
Publisher: John Wiley & Sons
ISBN: 1119106451
Category : Business & Economics
Languages : en
Pages : 258
Book Description
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.