Author | : Malik Ghallab |
Publisher | : Elsevier |
Total Pages | : 665 |
Release | : 2004-05-03 |
Genre | : Business & Economics |
ISBN | : 1558608567 |
Publisher Description
Author | : Malik Ghallab |
Publisher | : Elsevier |
Total Pages | : 665 |
Release | : 2004-05-03 |
Genre | : Business & Economics |
ISBN | : 1558608567 |
Publisher Description
Author | : Malik Ghallab |
Publisher | : Cambridge University Press |
Total Pages | : 373 |
Release | : 2016-08-09 |
Genre | : Computers |
ISBN | : 1107037271 |
This book presents the most recent and advanced techniques for creating autonomous AI systems capable of planning and acting effectively.
Author | : Hector Radanovic |
Publisher | : Springer Nature |
Total Pages | : 132 |
Release | : 2022-05-31 |
Genre | : Computers |
ISBN | : 3031015649 |
Planning is the model-based approach to autonomous behavior where the agent behavior is derived automatically from a model of the actions, sensors, and goals. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are intractable in the worst case when represented in compact form. In this book, we look at a variety of models used in AI planning, and at the methods that have been developed for solving them. The goal is to provide a modern and coherent view of planning that is precise, concise, and mostly self-contained, without being shallow. For this, we make no attempt at covering the whole variety of planning approaches, ideas, and applications, and focus on the essentials. The target audience of the book are students and researchers interested in autonomous behavior and planning from an AI, engineering, or cognitive science perspective. Table of Contents: Preface / Planning and Autonomous Behavior / Classical Planning: Full Information and Deterministic Actions / Classical Planning: Variations and Extensions / Beyond Classical Planning: Transformations / Planning with Sensing: Logical Models / MDP Planning: Stochastic Actions and Full Feedback / POMDP Planning: Stochastic Actions and Partial Feedback / Discussion / Bibliography / Author's Biography
Author | : A. Sima Uyar |
Publisher | : Springer |
Total Pages | : 311 |
Release | : 2013-07-12 |
Genre | : Technology & Engineering |
ISBN | : 3642393047 |
Solving scheduling problems has long presented a challenge for computer scientists and operations researchers. The field continues to expand as researchers and practitioners examine ever more challenging problems and develop automated methods capable of solving them. This book provides 11 case studies in automated scheduling, submitted by leading researchers from across the world. Each case study examines a challenging real-world problem by analysing the problem in detail before investigating how the problem may be solved using state of the art techniques.The areas covered include aircraft scheduling, microprocessor instruction scheduling, sports fixture scheduling, exam scheduling, personnel scheduling and production scheduling. Problem solving methodologies covered include exact as well as (meta)heuristic approaches, such as local search techniques, linear programming, genetic algorithms and ant colony optimisation.The field of automated scheduling has the potential to impact many aspects of our lives and work; this book highlights contributions to the field by world class researchers.
Author | : Tien-Chien Chang |
Publisher | : Prentice Hall |
Total Pages | : 246 |
Release | : 1985 |
Genre | : Business & Economics |
ISBN | : |
Author | : Rongfang Liu |
Publisher | : John Wiley & Sons |
Total Pages | : 228 |
Release | : 2016-09-23 |
Genre | : Science |
ISBN | : 1119289882 |
A comprehensive discussion of automated transit This book analyzes the successful implementations of automated transit in various international locations, such as Paris, Toronto, London, and Kuala Lumpur, and investigates the apparent lack of automated transit applications in the urban environment in the United States. The book begins with a brief definition of automated transit and its historical development. After a thorough description of the technical specifications, the author highlights a few applications from each sub-group of the automated transit spectrum. International case studies display various technologies and their applications, and identify vital factors that affect each system and performance evaluations of existing applications. The book then discusses the planning and operation of automated transit applications at both macro and micro levels. Finally, the book covers a number of less successful concepts, as well as the lessons learned, allowing readers to gain a comprehensive understanding of the topic. Key features: Provides a thorough examination of automated transit applications, their impact and implications for society Written by the committee chair for the Automated Transit Systems Transportation, Research Board Offers essential information on planning, costs, and applications of automated transit systems Covers driverless metros, automated LRT, group and personal rapid transit, a review of worldwide applications Includes capacity and safety guidelines, as well as vehicles, propulsion, and communication and control systems This book is essential reading for engineers, researchers, scientists, college or graduate students who work in transportation planning, engineering, operation and management fields.
Author | : Steven M. LaValle |
Publisher | : Cambridge University Press |
Total Pages | : 844 |
Release | : 2006-05-29 |
Genre | : Computers |
ISBN | : 9780521862059 |
Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.
Author | : Craig Knoblock |
Publisher | : Springer Science & Business Media |
Total Pages | : 194 |
Release | : 1993-01-31 |
Genre | : Computers |
ISBN | : 9780792393108 |
Generating Abstraction Hierarchies presents a completely automated approach to generating abstractions for problem solving. The abstractions are generated using a tractable, domain-independent algorithm whose only inputs are the definition of a problem space and the problem to be solved and whose output is an abstraction hierarchy that is tailored to the particular problem. The algorithm generates abstraction hierarchies that satisfy the `ordered monotonicity' property, which guarantees that the structure of an abstract solution is not changed in the process of refining it. An abstraction hierarchy with this property allows a problem to be decomposed such that the solution in an abstract space can be held invariant while the remaining parts of a problem are solved. The algorithm for generating abstractions is implemented in a system called ALPINE, which generates abstractions for a hierarchical version of the PRODIGY problem solver. Generating Abstraction Hierarchies formally defines this hierarchical problem solving method, shows that under certain assumptions this method can reduce the size of a search space from exponential to linear in the solution size, and describes the implementation of this method in PRODIGY. The abstractions generated by ALPINE are tested in multiple domains on large problem sets and are shown to produce shorter solutions with significantly less search than problem solving without using abstraction. Generating Abstraction Hierarchies will be of interest to researchers in machine learning, planning and problem reformation.
Author | : Ioannis Vlahavas |
Publisher | : IGI Global |
Total Pages | : 384 |
Release | : 2005-01-01 |
Genre | : Business & Economics |
ISBN | : 9781591404514 |
The Intelligent Techniques for Planning presents a number of modern approaches to the area of automated planning. These approaches combine methods from classical planning such as the construction of graphs and the use of domain-independent heuristics with techniques from other areas of artificial intelligence. This book discuses, in detail, a number of state-of-the-art planning systems that utilize constraint satisfaction techniques in order to deal with time and resources, machine learning in order to utilize experience drawn from past runs, methods from knowledge systems for more expressive representation of knowledge and ideas from other areas such as Intelligent Agents. Apart from the thorough analysis and implementation details, each chapter of the book also provides extensive background information about its subject and presents and comments on similar approaches done in the past.