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| 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 | : Malik Ghallab |
| Publisher | : Elsevier |
| Total Pages | : 665 |
| Release | : 2004-05-03 |
| Genre | : Business & Economics |
| ISBN | : 1558608567 |
Publisher Description
| 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 | : 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 | : Tien-Chien Chang |
| Publisher | : Prentice Hall |
| Total Pages | : 246 |
| Release | : 1985 |
| Genre | : Business & Economics |
| ISBN | : |
| Author | : Steven Michael LaValle |
| Publisher | : |
| Total Pages | : 826 |
| Release | : 2006 |
| Genre | : Algorithms |
| ISBN | : 9780511241338 |
Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that integrates literature from several fields into a coherent source for teaching and reference in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications, and medicine.
| Author | : Malik Ghallab |
| Publisher | : Elsevier |
| Total Pages | : 635 |
| Release | : 2004-05-21 |
| Genre | : Computers |
| ISBN | : 0080490514 |
Automated planning technology now plays a significant role in a variety of demanding applications, ranging from controlling space vehicles and robots to playing the game of bridge. These real-world applications create new opportunities for synergy between theory and practice: observing what works well in practice leads to better theories of planning, and better theories lead to better performance of practical applications. Automated Planning mirrors this dialogue by offering a comprehensive, up-to-date resource on both the theory and practice of automated planning. The book goes well beyond classical planning, to include temporal planning, resource scheduling, planning under uncertainty, and modern techniques for plan generation, such as task decomposition, propositional satisfiability, constraint satisfaction, and model checking. The authors combine over 30 years experience in planning research and development to offer an invaluable text to researchers, professionals, and graduate students. Provides a thorough understanding of AI planning theory and practice, and how they relate to each other Covers all the contemporary topics of planning, as well as important practical applications of planning, such as model checking and game playing Presents case studies and applications in planning engineering, space, robotics, CAD/CAM, process control, emergency operations, and games Provides lecture notes, examples of programming assignments, pointers to downloadable planning systems and related information online
| Author | : Craig A. Knoblock |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 179 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461531527 |
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 | : Kiyoji Asai |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 566 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3642835902 |
The Current state of expectations is that Computer Integrated Manufacturing (CIM) will ulti mately determine the industrial growth of world nations within the next few decades. Computer Aided Design (CAD), Computer Aided Manufacturing (CAM), Flexible Manufacturing Systems (FMS), Robotics together with Knowledge and Information Based Systems (KIBS) and Com munication Networks are expected to develop to a mature state to respond effectively to the managerial requirements of the factories of the future that are becoming highly integrated and complex. CIM represents a new production approach which will allow the factories to deliver a high variety of products at a low cost and with short production cycles. The new technologies for CIM are needed to develop manufacturing environments that are smarter, faster, close-cou pled, integrated, optimized, and flexible. Sophistication and a high degree of specialization in materials science, artificial intelligence, communications technology and knowledge-information science techniques are needed among others for the development of realizable and workable CIM systems that are capable of adjusting to volatile markets. CIM factories are to allow the production of a wide variety of similar products in small batches through standard but multi mission oriented designs that accommodate flexibility with specialized software.
| Author | : |
| Publisher | : |
| Total Pages | : |
| Release | : 2020 |
| Genre | : Artificial intelligence |
| ISBN | : 9783030385620 |
This book presents a comprehensive review for Knowledge Engineering tools and techniques that can be used in Artificial Intelligence Planning and Scheduling. KE tools can be used to aid in the acquisition of knowledge and in the construction of domain models, which this book will illustrate. AI planning engines require a domain model which captures knowledge about how a particular domain works - e.g. the objects it contains and the available actions that can be used. However, encoding a planning domain model is not a straightforward task - a domain expert may be needed for their insight into the domain but this information must then be encoded in a suitable representation language. The development of such domain models is both time-consuming and error-prone. Due to these challenges, researchers have developed a number of automated tools and techniques to aid in the capture and representation of knowledge. This book targets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.
