Accelerating Heuristic Search For Ai Planning

Download Accelerating Heuristic Search For Ai Planning full books in PDF, epub, and Kindle. Read online Accelerating Heuristic Search For Ai Planning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Accelerating Heuristic Search for AI Planning

Author : You Xu
Publisher :
ISBN 13 :
Total Pages : 134 pages
Book Rating : 4.:/5 (919 download)

DOWNLOAD NOW!

Book Synopsis Accelerating Heuristic Search for AI Planning by : You Xu

Download or read book Accelerating Heuristic Search for AI Planning written by You Xu and published by . This book was released on 2014 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI Planning is an important research field. Heuristic search is the most commonly used method in solving planning problems. Despite recent advances in improving the quality of heuristics and devising better search strategies, the high computational cost of heuristic search remains a barrier that severely limits its application to real world problems. In this dissertation, we propose theories, algorithms and systems to accelerate heuristic search for AI planning. We make four major contributions in this dissertation. First, we propose a state-space reduction method called Stratified Planning to accelerate heuristic search. Stratified Planning can be combined with any heuristic search to prune redundant paths in state space, without sacrificing the optimality and completeness of search algorithms. Second, we propose a general theory for partial order reduction in planning. The proposed theory unifies previous reduction algorithms for planning, and ushers in new partial order reduction algorithms that can further accelerate heuristic search by pruning more nodes in state space than previously proposed algorithms. Third, we study the local structure of state space and propose using random walks to accelerate plateau exploration for heuristic search. We also implement two state-of-the-art planners that perform competitively in the Seventh International Planning Competition. Last, we utilize cloud computing to further accelerate search for planning. We propose a portfolio stochastic search algorithm that takes advantage of the cloud. We also implement a cloud-based planning system to which users can submit planning tasks and make full use of the computational resources provided by the cloud. We push the state of the art in AI planning by developing theories and algorithms that can accelerate heuristic search for planning. We implement state-of-the-art planning systems that have strong speed and quality performance.

Planning Algorithms

Author : Steven M. LaValle
Publisher : Cambridge University Press
ISBN 13 : 9780521862059
Total Pages : 844 pages
Book Rating : 4.8/5 (62 download)

DOWNLOAD NOW!

Book Synopsis Planning Algorithms by : Steven M. LaValle

Download or read book Planning Algorithms written by Steven M. LaValle and published by Cambridge University Press. This book was released on 2006-05-29 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Heuristic Search

Author : Stefan Edelkamp
Publisher : Elsevier
ISBN 13 : 0080919731
Total Pages : 865 pages
Book Rating : 4.0/5 (89 download)

DOWNLOAD NOW!

Book Synopsis Heuristic Search by : Stefan Edelkamp

Download or read book Heuristic Search written by Stefan Edelkamp and published by Elsevier. This book was released on 2011-05-31 with total page 865 pages. Available in PDF, EPUB and Kindle. Book excerpt: Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. - Provides real-world success stories and case studies for heuristic search algorithms - Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units

Empirical Models of Heuristic Search in AI Planning and Neural Sequence Decoding

Author : Eldan Cohen
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)

DOWNLOAD NOW!

Book Synopsis Empirical Models of Heuristic Search in AI Planning and Neural Sequence Decoding by : Eldan Cohen

Download or read book Empirical Models of Heuristic Search in AI Planning and Neural Sequence Decoding written by Eldan Cohen and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heuristic search algorithms are widely used in both AI planning and the decoding of sequences from deep neural networks. In recent years, several lines of work have highlighted different factors that impact the empirical performance of heuristic search algorithms. However, a principled empirical understanding of the search behavior of these heuristic search algorithms has yet to be developed. Empirical models, such as the phase transition and the heavy-tailed behavior, have been central to the development of empirical understanding of combinatorial search problems such as constraint satisfaction problems (CSP) and satisfiability (SAT). In this dissertation, we investigate the use of empirical models to explain the behavior of heuristic search algorithms in AI planning and neural sequence decoding and support the development of more efficient search algorithms. In AI planning, we develop empirical models for problem difficulty of greedy best first (GBFS), the most commonly used algorithm for satisficing planning. First, we establish the existence of a phase transition in the solubility of planning problems and investigate its implications to problem difficulty. Then, we demonstrate the heavy-tailed behavior of GBFS and provide a deeper understanding of the connection between constrainedness and local minima. Informed by our analysis, we develop a novel variant of GBFS that outperforms the baseline. In neural sequence decoding, we develop empirical models for the performance of beam search, the ubiquitous algorithm for decoding deep sequence models. First, we investigate the empirical problem of performance degradation in beam search. We present an explanatory model based on search discrepancies that generalizes previous observations on the behavior of beam search. Building on our analysis, we present two heuristic techniques that eliminate the problem. Next, we study goal-oriented sequence decoding and show that, similar to GBFS, we observe heavy-tailed behavior. We present a novel variant of goal-oriented beam search that exploits our insights and outperforms the baseline. Our work shows the importance of empirical models in the study and development of heuristic search algorithms and demonstrates that empirical models developed for CSPs and SAT can be adapted to AI planning and neural sequence decoding.

KI 2004: Advances in Artificial Intelligence

Author : Susanne Biundo
Publisher : Springer
ISBN 13 : 3540302212
Total Pages : 477 pages
Book Rating : 4.5/5 (43 download)

DOWNLOAD NOW!

Book Synopsis KI 2004: Advances in Artificial Intelligence by : Susanne Biundo

Download or read book KI 2004: Advances in Artificial Intelligence written by Susanne Biundo and published by Springer. This book was released on 2005-01-11 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: KI2004wasthe27theditionoftheannualGermanConferenceonArti?cialInt- ligence, which traditionally brings together academic and industrial researchers from all areas of AI and which enjoys increasing international attendance. KI 2004 received 103 submissions from 26 countries. This volume contains the 30 papers that were?nally selected for presentation at the conference. The papers cover quite a broad spectrum of "classical" subareas of AI, like na- ral language processing, neural networks, knowledge representation, reasoning, planning, and search. When looking at this year's contributions, it was exciting to observe that there was a strong trend towards actual real-world applications of AI technology. A majority of contributions resulted from or were motivated by applications in a variety of areas. Examples include applications of pl- ning, where the technology is being exploited for taxiway tra?c control and game playing; natural language processing and knowledge representation are enabling advanced Web-based information processing; and the integration of - sults from automated reasoning, neural networks and machine perception into robotics leads to signi?cantly improved capabilities of autonomous systems. The technical programme of KI 2004 was highlighted by invited talks from outstanding researchers in the areas of automated reasoning, robot planning, constraintreasoning, machinelearning, andsemanticWeb:Jorg · Siekmann(DFKI andUniversityofSaarland, Saarbruc · ken), MalikGhallab(LAAS-CNRS, Toulouse), Franco ı is Fages (INRIA Rocquencourt), Martin Riedmiller (University of - nabru ·ck), andWolfgangWahlster(DFKIandUniversityofSaarland, Saarbruc · ken). Their invited papers are also presented in this volume

Abstraction, Reformulation, and Approximation

Author : Sven Koenig
Publisher : Springer
ISBN 13 : 3540456228
Total Pages : 360 pages
Book Rating : 4.5/5 (44 download)

DOWNLOAD NOW!

Book Synopsis Abstraction, Reformulation, and Approximation by : Sven Koenig

Download or read book Abstraction, Reformulation, and Approximation written by Sven Koenig and published by Springer. This book was released on 2003-08-02 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: It has been recognized since the inception of Artificial Intelligence (AI) that abstractions, problem reformulations, and approximations (AR&A) are central to human common sense reasoning and problem solving and to the ability of systems to reason effectively in complex domains. AR&A techniques have been used to solve a variety of tasks, including automatic programming, constraint satisfaction, design, diagnosis, machine learning, search, planning, reasoning, game playing, scheduling, and theorem proving. The primary purpose of AR&A techniques in such settings is to overcome computational intractability. In addition, AR&A techniques are useful for accelerating learning and for summarizing sets of solutions. This volume contains the proceedings of SARA 2002, the fifth Symposium on Abstraction, Reformulation, and Approximation, held at Kananaskis Mountain Lodge, Kananaskis Village, Alberta (Canada), August 2 4, 2002. The SARA series is the continuation of two separate threads of workshops: AAAI workshops in 1990 and 1992, and an ad hoc series beginning with the "Knowledge Compilation" workshop in 1986 and the "Change of Representation and Inductive Bias" workshop in 1988 with followup workshops in 1990 and 1992. The two workshop series merged in 1994 to form the first SARA. Subsequent SARAs were held in 1995, 1998, and 2000.

Modelling Autonomic Communication Environments

Author : Rob Brennan
Publisher : Springer Science & Business Media
ISBN 13 : 3642168353
Total Pages : 134 pages
Book Rating : 4.6/5 (421 download)

DOWNLOAD NOW!

Book Synopsis Modelling Autonomic Communication Environments by : Rob Brennan

Download or read book Modelling Autonomic Communication Environments written by Rob Brennan and published by Springer Science & Business Media. This book was released on 2010-10-19 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th IEEE International Workshop on Modelling Autonomic Communications Environments, MACE 2010, held in Niagara Falls, Canada, in October 2010, as part of the 6th International Conference on Network and Service Management, CNSM 2010. The 10 full papers presented were carefully reviewed and selected from 17 submissions. The papers are organized in topical sections on autonomics in home area networks and multimedia; ontologies, experience, adaptive systems and federation; and modeling for virtualized infrastructure.

Utilizing Problem Structure in Planning

Author : Jörg Hoffmann
Publisher : Springer
ISBN 13 : 3540396071
Total Pages : 258 pages
Book Rating : 4.5/5 (43 download)

DOWNLOAD NOW!

Book Synopsis Utilizing Problem Structure in Planning by : Jörg Hoffmann

Download or read book Utilizing Problem Structure in Planning written by Jörg Hoffmann and published by Springer. This book was released on 2003-10-24 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Planning is a crucial skill for any autonomous agent, be it a physically embedded agent, such as a robot, or a purely simulated software agent. For this reason, planning, as a central research area of artificial intelligence from its beginnings, has gained even more attention and importance recently. After giving a general introduction to AI planning, the book describes and carefully evaluates the algorithmic techniques used in fast-forward planning systems (FF), demonstrating their excellent performance in many wellknown benchmark domains. In advance, an original and detailed investigation identifies the main patterns of structure which cause the performance of FF, categorizing planning domains in a taxonomy of different classes with respect to their aptitude for being solved by heuristic approaches, such as FF. As shown, the majority of the planning benchmark domains lie in classes which are easy to solve.

Web Services Foundations

Author : Athman Bouguettaya
Publisher : Springer Science & Business Media
ISBN 13 : 146147518X
Total Pages : 740 pages
Book Rating : 4.4/5 (614 download)

DOWNLOAD NOW!

Book Synopsis Web Services Foundations by : Athman Bouguettaya

Download or read book Web Services Foundations written by Athman Bouguettaya and published by Springer Science & Business Media. This book was released on 2013-09-04 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Web services and Service-Oriented Computing (SOC) have become thriving areas of academic research, joint university/industry research projects, and novel IT products on the market. SOC is the computing paradigm that uses Web services as building blocks for the engineering of composite, distributed applications out of the reusable application logic encapsulated by Web services. Web services could be considered the best-known and most standardized technology in use today for distributed computing over the Internet. Web Services Foundations is the first installment of a two-book collection covering the state-of-the-art of both theoretical and practical aspects of Web services and SOC research. This book specifically focuses on the foundations of Web services and SOC and covers - among others - Web service composition, non-functional aspects of Web services, Web service selection and recommendation, and assisted Web service composition. The editors collect advanced topics in the second book of the collection, Advanced Web Services, (Springer, 2013). Both books together comprise approximately 1400 pages and are the result of an enormous community effort that involved more than 100 authors, comprising the world’s leading experts in this field.

Intelligent Techniques for Planning

Author : Ioannis Vlahavas
Publisher : IGI Global
ISBN 13 : 1591404525
Total Pages : 364 pages
Book Rating : 4.5/5 (914 download)

DOWNLOAD NOW!

Book Synopsis Intelligent Techniques for Planning by : Ioannis Vlahavas

Download or read book Intelligent Techniques for Planning written by Ioannis Vlahavas and published by IGI Global. This book was released on 2005-01-01 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

KI 2017: Advances in Artificial Intelligence

Author : Gabriele Kern-Isberner
Publisher : Springer
ISBN 13 : 3319671901
Total Pages : 411 pages
Book Rating : 4.3/5 (196 download)

DOWNLOAD NOW!

Book Synopsis KI 2017: Advances in Artificial Intelligence by : Gabriele Kern-Isberner

Download or read book KI 2017: Advances in Artificial Intelligence written by Gabriele Kern-Isberner and published by Springer. This book was released on 2017-09-18 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 40th Annual German Conference on Artificial Intelligence, KI 2017 held in Dortmund, Germany in September 2017. The 20 revised full technical papers presented together with 16 short technical communications were carefully reviewed and selected from 73 submissions. The conference cover a range of topics from, e. g., agents, robotics, cognitive sciences, machine learning, planning, knowledge representation, reasoning, and ontologies, with numerous applications in areas like social media, psychology, transportation systems and reflecting the richness and diversity of their field.

Automated Planning and Acting

Author : Malik Ghallab
Publisher : Cambridge University Press
ISBN 13 : 1107037271
Total Pages : 373 pages
Book Rating : 4.1/5 (7 download)

DOWNLOAD NOW!

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.

Exploring Artificial Intelligence in the New Millennium

Author : Gerhard Lakemeyer
Publisher : Morgan Kaufmann
ISBN 13 : 9781558608115
Total Pages : 424 pages
Book Rating : 4.6/5 (81 download)

DOWNLOAD NOW!

Book Synopsis Exploring Artificial Intelligence in the New Millennium by : Gerhard Lakemeyer

Download or read book Exploring Artificial Intelligence in the New Millennium written by Gerhard Lakemeyer and published by Morgan Kaufmann. This book was released on 2003 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guide is a unique presentation of the spectrum of ongoing research in Artificial Intelligence. An ideal collection for personal reference or for use in introductory courses in AI and its subfields, "Exploring Artificial Intelligence in the New Millennium" is essential reading for anyone interested in the intellectual and technological challenges of AI.

Mining Intelligence and Knowledge Exploration

Author : Rajendra Prasath
Publisher : Springer
ISBN 13 : 3319268325
Total Pages : 731 pages
Book Rating : 4.3/5 (192 download)

DOWNLOAD NOW!

Book Synopsis Mining Intelligence and Knowledge Exploration by : Rajendra Prasath

Download or read book Mining Intelligence and Knowledge Exploration written by Rajendra Prasath and published by Springer. This book was released on 2016-01-02 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2015, held in Hyderabad, India, in December 2015. The 48 full papers and 8 short papers presented together with 4 doctoral consortium papers were carefully reviewed and selected from 185 submissions. The papers cover a wide range of topics including information retrieval, machine learning, pattern recognition, knowledge discovery, classification, clustering, image processing, network security, speech processing, natural language processing, language, cognition and computation, fuzzy sets, and business intelligence.

Introduction to Symbolic Plan and Goal Recognition

Author : Reuth Mirsky
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1636390420
Total Pages : 122 pages
Book Rating : 4.6/5 (363 download)

DOWNLOAD NOW!

Book Synopsis Introduction to Symbolic Plan and Goal Recognition by : Reuth Mirsky

Download or read book Introduction to Symbolic Plan and Goal Recognition written by Reuth Mirsky and published by Morgan & Claypool Publishers. This book was released on 2021-01-28 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a high-level introduction and overview of plan and goal recognition including the core elements and practical advice for modeling them. Along with activity recognition, these areas of research play a crucial role in a wide variety of applications including assistive technology, software assistants, computer and network security, human-robot collaboration, natural language processing, video games, and much more. This synergistic area of research combines, unites, and makes use of techniques and research from a wide range of areas including user modeling, machine vision, automated planning, intelligent user interfaces, human-computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning. This wide range of applications and disciplines has produced a wealth of ideas, models, tools, and results in the recognition literature. However, it has also contributed to fragmentation in the field, with researchers publishing relevant results in a wide spectrum of journals and conferences. This book seeks to address this fragmentation by providing a high-level introduction and historical overview of the plan and goal recognition literature. It provides a description of the core elements that comprise these recognition problems and practical advice for modeling them. In particular, we define and distinguish the different recognition tasks. We formalize the major approaches to modeling these problems using a single motivating example. Finally, we describe a number of state-of-the-art systems and their extensions, future challenges, and some potential applications.

Knowledge Engineering Tools and Techniques for AI Planning

Author : Mauro Vallati
Publisher : Springer Nature
ISBN 13 : 3030385612
Total Pages : 277 pages
Book Rating : 4.0/5 (33 download)

DOWNLOAD NOW!

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.

Speeding Up the Convergence of Online Heuristic Search and Scaling Up Offline Heuristic Search

Author : David Andre Furcy
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (575 download)

DOWNLOAD NOW!

Book Synopsis Speeding Up the Convergence of Online Heuristic Search and Scaling Up Offline Heuristic Search by : David Andre Furcy

Download or read book Speeding Up the Convergence of Online Heuristic Search and Scaling Up Offline Heuristic Search written by David Andre Furcy and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The most popular methods for solving the shortest-path problem in Artificial Intelligence are heuristic search algorithms. The main contributions of this research are new heuristic search algorithms that are either faster or scale up to larger problems than existing algorithms. Our contributions apply to both online and offline tasks. For online tasks, existing real-time heuristic search algorithms learn better informed heuristic values and in some cases eventually converge to a shortest path by repeatedly executing the action leading to a successor state with a minimum cost-to-goal estimate. In contrast, we claim that real-time heuristic search converges faster to a shortest path when it always selects an action leading to a state with a minimum f-value, where the f-value of a state is an estimate of the cost of a shortest path from start to goal via the state, just like in the offline A* search algorithm. We support this claim by implementing this new non-trivial action-selection rule in FALCONS and by showing empirically that FALCONS significantly reduces the number of actions to convergence of a state-of-the-art real-time search algorithm. For offline tasks, we improve on two existing ways of scaling up best-first search to larger problems. First, it is known that the WA* algorithm (a greedy variant of A*) solves larger problems when it is either diversified (i.e., when it performs expansions in parallel) or committed (i.e., when it chooses the state to expand next among a fixed-size subset of the set of generated but unexpanded states). We claim that WA* solves even larger problems when it is enhanced with both diversity and commitment. We support this claim with our MSC-KWA* algorithm. Second, it is known that breadth-first search solves larger problems when it prunes unpromising states, resulting in the beam search algorithm. We claim that beam search quickly solves even larger problems when it is enhanced with backtracking based on limited discrepancy search. We support this claim with our BULB algorithm. We show that both MSC-KWA* and BULB scale up to larger problems than several state-of-the-art offline search algorithms in three standard benchmark domains. Finally, we present an anytime variant of BULB and apply it to the multiple sequence alignment problem in biology.