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This book presents the most recent and advanced techniques for creating autonomous AI systems capable of planning and acting effectively.
Book Synopsis Automated Planning and Acting by : Malik Ghallab
Download or read book Automated Planning and Acting written by Malik Ghallab and published by Cambridge University Press. This book was released on 2016-08-09 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most recent and advanced techniques for creating autonomous AI systems capable of planning and acting effectively.
Book Synopsis Automated Planning by : Malik Ghallab
Download or read book Automated Planning written by Malik Ghallab and published by Elsevier. This book was released on 2004-05-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description
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.
Book Synopsis Automated Scheduling and Planning by : A. Sima Uyar
Download or read book Automated Scheduling and Planning written by A. Sima Uyar and published by Springer. This book was released on 2013-07-12 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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
Book Synopsis A Concise Introduction to Models and Methods for Automated Planning by : Hector Radanovic
Download or read book A Concise Introduction to Models and Methods for Automated Planning written by Hector Radanovic and published by Springer Nature. This book was released on 2022-05-31 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
This book deals with the problems related to planning motion laws and t- jectories for the actuation system of automatic machines, in particular for those based on electric drives, and robots. The problem of planning suitable trajectories is relevant not only for the proper use of these machines, in order to avoid undesired e?ects such as vibrations or even damages on the mech- ical structure, but also in some phases of their design and in the choice and sizing of the actuators. This is particularly true now that the concept of “el- tronic cams” has replaced, in the design of automatic machines, the classical approach based on “mechanical cams”. The choice of a particular trajectory has direct and relevant implications on several aspects of the design and use of an automatic machine, like the dimensioning of the actuators and of the reduction gears, the vibrations and e?orts generated on the machine and on the load, the tracking errors during the motion execution. For these reasons, in order to understand and appreciate the peculiarities of the di?erent techniques available for trajectory planning, besides the ma- ematical aspects of their implementation also a detailed analysis in the time and frequency domains, a comparison of their main properties under di?erent points of view, and general considerations related to their practical use are reported.
Book Synopsis Trajectory Planning for Automatic Machines and Robots by : Luigi Biagiotti
Download or read book Trajectory Planning for Automatic Machines and Robots written by Luigi Biagiotti and published by Springer Science & Business Media. This book was released on 2008-10-23 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the problems related to planning motion laws and t- jectories for the actuation system of automatic machines, in particular for those based on electric drives, and robots. The problem of planning suitable trajectories is relevant not only for the proper use of these machines, in order to avoid undesired e?ects such as vibrations or even damages on the mech- ical structure, but also in some phases of their design and in the choice and sizing of the actuators. This is particularly true now that the concept of “el- tronic cams” has replaced, in the design of automatic machines, the classical approach based on “mechanical cams”. The choice of a particular trajectory has direct and relevant implications on several aspects of the design and use of an automatic machine, like the dimensioning of the actuators and of the reduction gears, the vibrations and e?orts generated on the machine and on the load, the tracking errors during the motion execution. For these reasons, in order to understand and appreciate the peculiarities of the di?erent techniques available for trajectory planning, besides the ma- ematical aspects of their implementation also a detailed analysis in the time and frequency domains, a comparison of their main properties under di?erent points of view, and general considerations related to their practical use are reported.
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.
Book Synopsis Knowledge Engineering Tools and Techniques for AI Planning by : Mauro Vallati
Download or read book Knowledge Engineering Tools and Techniques for AI Planning written by Mauro Vallati and published by Springer Nature. This book was released on 2020-03-25 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis An Introduction to Automated Process Planning Systems by : Tien-Chien Chang
Download or read book An Introduction to Automated Process Planning Systems written by Tien-Chien Chang and published by Prentice Hall. This book was released on 1985 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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
Book Synopsis Automated Planning by : Malik Ghallab
Download or read book Automated Planning written by Malik Ghallab and published by Elsevier. This book was released on 2004-05-21 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
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.
Book Synopsis Planning Algorithms by : Steven Michael LaValle
Download or read book Planning Algorithms written by Steven Michael LaValle and published by . This book was released on 2006 with total page 826 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
Book Synopsis Generating Abstraction Hierarchies by : Craig A. Knoblock
Download or read book Generating Abstraction Hierarchies written by Craig A. Knoblock and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
