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Autonomous Search

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Release : 2012-01-05
Genre : Computers
Kind : eBook
Book Rating : 347/5 ( reviews)

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Book Synopsis Autonomous Search by : Youssef Hamadi

Download or read book Autonomous Search written by Youssef Hamadi. This book was released on 2012-01-05. Available in PDF, EPUB and Kindle. Book excerpt: Decades of innovations in combinatorial problem solving have produced better and more complex algorithms. These new methods are better since they can solve larger problems and address new application domains. They are also more complex which means that they are hard to reproduce and often harder to fine-tune to the peculiarities of a given problem. This last point has created a paradox where efficient tools are out of reach of practitioners. Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality consist in the fact that problem solvers can now perform self-improvement operations based on analysis of the performances of the solving process -- including short-term reactive reconfiguration and long-term improvement through self-analysis of the performance, offline tuning and online control, and adaptive control and supervised control. Autonomous search "crosses the chasm" and provides engineers and practitioners with systems that are able to autonomously self-tune their performance while effectively solving problems. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality consist in the fact that problem solvers can now perform self-improvement operations based on analysis of the performances of the solving process -- including short-term reactive reconfiguration and long-term improvement through self-analysis of the performance, offline tuning and online control, and adaptive control and supervised control. Autonomous search "crosses the chasm" and provides engineers and practitioners with systems that are able to autonomously self-tune their performance while effectively solving problems. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms.

Real-Time Search for Learning Autonomous Agents

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Release : 1997-06-30
Genre : Computers
Kind : eBook
Book Rating : 447/5 ( reviews)

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Book Synopsis Real-Time Search for Learning Autonomous Agents by : Toru Ishida

Download or read book Real-Time Search for Learning Autonomous Agents written by Toru Ishida. This book was released on 1997-06-30. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous agents or multiagent systems are computational systems in which several computational agents interact or work together to perform some set of tasks. These systems may involve computational agents having common goals or distinct goals. Real-Time Search for Learning Autonomous Agents focuses on extending real-time search algorithms for autonomous agents and for a multiagent world. Although real-time search provides an attractive framework for resource-bounded problem solving, the behavior of the problem solver is not rational enough for autonomous agents. The problem solver always keeps the record of its moves and the problem solver cannot utilize and improve previous experiments. Other problems are that although the algorithms interleave planning and execution, they cannot be directly applied to a multiagent world. The problem solver cannot adapt to the dynamically changing goals and the problem solver cannot cooperatively solve problems with other problem solvers. This book deals with all these issues. Real-Time Search for Learning Autonomous Agents serves as an excellent resource for researchers and engineers interested in both practical references and some theoretical basis for agent/multiagent systems. The book can also be used as a text for advanced courses on the subject.

The Autonomous Web

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Release : 2022-01-01
Genre : Computers
Kind : eBook
Book Rating : 360/5 ( reviews)

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Book Synopsis The Autonomous Web by : Herwig Unger

Download or read book The Autonomous Web written by Herwig Unger. This book was released on 2022-01-01. Available in PDF, EPUB and Kindle. Book excerpt: This book initiates a transformation of the Web into a self-managing, autonomous information system to challenge today’s all-embracing role of big search engines as centralized information managers. In the last decades, the World Wide Web became the biggest source for all kinds of information needed. After a short review of the state of the art, a Web-based system is presented for the first time, which employs all its instances equally to provide, consume, and process information uniformly and consistently. In order to build such an efficient, decentralized, and fully integrated information space with all its needed functionalities, a set of diverse algorithms is introduced. These novel mechanisms for load balancing, routing, clustering, document classification, but also time-dependent information management pertain to almost all system levels. Finally, three different approaches to decentralized Web search are discussed that represent the backbone of the new autonomous Web.

Modelling of Autonomous Search and Rescue Missions by Interval-Valued Neutrosophic WASPAS Framework

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Release :
Genre : Mathematics
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Modelling of Autonomous Search and Rescue Missions by Interval-Valued Neutrosophic WASPAS Framework by : Rokas Semenas

Download or read book Modelling of Autonomous Search and Rescue Missions by Interval-Valued Neutrosophic WASPAS Framework written by Rokas Semenas . This book was released on . Available in PDF, EPUB and Kindle. Book excerpt: The application of autonomous robots in search and rescue missions represents a complex task which requires a robot to make robust decisions in unknown and dangerous environments. However, imprecise robot movements and small measurement errors obtained by robot sensors can have an impact on the autonomous environment exploration quality, and therefore, should be addressed while designing search and rescue (SAR) robots.

Search and Classification Using Multiple Autonomous Vehicles

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Release : 2012-04-02
Genre : Technology & Engineering
Kind : eBook
Book Rating : 563/5 ( reviews)

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Book Synopsis Search and Classification Using Multiple Autonomous Vehicles by : Yue Wang

Download or read book Search and Classification Using Multiple Autonomous Vehicles written by Yue Wang. This book was released on 2012-04-02. Available in PDF, EPUB and Kindle. Book excerpt: Search and Classification Using Multiple Autonomous Vehicles provides a comprehensive study of decision-making strategies for domain search and object classification using multiple autonomous vehicles (MAV) under both deterministic and probabilistic frameworks. It serves as a first discussion of the problem of effective resource allocation using MAV with sensing limitations, i.e., for search and classification missions over large-scale domains, or when there are far more objects to be found and classified than there are autonomous vehicles available. Under such scenarios, search and classification compete for limited sensing resources. This is because search requires vehicle mobility while classification restricts the vehicles to the vicinity of any objects found. The authors develop decision-making strategies to choose between these competing tasks and vehicle-motion-control laws to achieve the proposed management scheme. Deterministic Lyapunov-based, probabilistic Bayesian-based, and risk-based decision-making strategies and sensor-management schemes are created in sequence. Modeling and analysis include rigorous mathematical proofs of the proposed theorems and the practical consideration of limited sensing resources and observation costs. A survey of the well-developed coverage control problem is also provided as a foundation of search algorithms within the overall decision-making strategies. Applications in both underwater sampling and space-situational awareness are investigated in detail. The control strategies proposed in each chapter are followed by illustrative simulation results and analysis. Academic researchers and graduate students from aerospace, robotics, mechanical or electrical engineering backgrounds interested in multi-agent coordination and control, in detection and estimation or in Bayes filtration will find this text of interest.

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