Symbolic Bidirectional Breadth-first Heuristic Search PDF Download
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Author: Simon Kim Richards
Publisher:
ISBN:
Category : Decision logic tables
Languages : en
Pages :
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Book Description
A Reduced Ordered Binary Decision Diagram (BDD) is a symbolic data structure introduced to the model checking community by Bryant in 1986 to help verify properties of systems with very large state spaces. Recently, BDDs have been used in heuristic search algorithms as an approach to representing and solving search problems with very large state spaces. However, these algorithms are still not memory efficient. This thesis presents a symbolic heuristic search algorithm that uses BDDs in a memory efficient way by performing bidirectional breadth-first heuristic search. The approach is evaluated empirically against existing symbolic methods and is shown to provide a significant improvement in performance.
Author: Simon Kim Richards
Publisher:
ISBN:
Category : Decision logic tables
Languages : en
Pages :
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Book Description
A Reduced Ordered Binary Decision Diagram (BDD) is a symbolic data structure introduced to the model checking community by Bryant in 1986 to help verify properties of systems with very large state spaces. Recently, BDDs have been used in heuristic search algorithms as an approach to representing and solving search problems with very large state spaces. However, these algorithms are still not memory efficient. This thesis presents a symbolic heuristic search algorithm that uses BDDs in a memory efficient way by performing bidirectional breadth-first heuristic search. The approach is evaluated empirically against existing symbolic methods and is shown to provide a significant improvement in performance.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
A Reduced Ordered Binary Decision Diagram (BDD) is a symbolic data structure introduced to the model checking community by Bryant in 1986 to help verify properties of systems with very large state spaces. Recently, BDDs have been used in heuristic search algorithms as an approach to representing and solving search problems with very large state spaces. However, these algorithms are still not memory efficient. This thesis presents a symbolic heuristic search algorithm that uses BDDs in a memory efficient way by performing bidirectional breadth-first heuristic search. The approach is evaluated empirically against existing symbolic methods and is shown to provide a significant improvement in performance.
Author: Stefan Edelkamp
Publisher: Elsevier
ISBN: 0080919731
Category : Computers
Languages : en
Pages : 865
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Book Description
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
Author: Bindu Bansal
Publisher: Laxmi Publications
ISBN: 9381159378
Category :
Languages : en
Pages : 371
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Book Description
Author: Andreas Dengel
Publisher: Springer
ISBN: 3540858458
Category : Computers
Languages : en
Pages : 416
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Book Description
KI 2008 was the 31st Annual German Conference on Arti?cial Intelligence held September 23–26 at the University of Kaiserslautern and the German Research Center for Arti?cial Intelligence DFKI GmbH in Kaiserslautern, Germany. The conference series started in 1975 with the German Workshop on AI (GWAI), which took place in Bonn, and represents the ?rst forum of its type for the German AI Community. Over the years AI has become a major ?eld in c- puter scienceinGermanyinvolvinga numberof successfulprojects thatreceived much international attention. Today KI conferences are international forums where participants from academia and industry from all over the world meet to exchange their recent research results and to discuss trends in the ?eld. Since 1993 the meeting has been called the “Annual German Conference on Arti?cial Intelligence,” designated by the German acronym KI. This volume contains the papers selected out of 77 submissions, including a number of submissions from outside German-speaking countries. In total, 15 submissions (19%) were accepted for oral and 30 (39%) for poster presentation. Oralpresentationsattheconferenceweresingletrack. Becauseofthis,thechoice of presentation form (oral, poster) was based on how well reviews indicated that the paper would ?t into one or the other format. The proceedings allocate the same space to both types of papers. In addition, we selected six papers that show high application potential - scribing systems or prototypical implementations of innovative AI technologies. They are also included in this volume as two-page extended abstracts.
Author: George Politowski
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 160
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Book Description
Author: Ira Pohl
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 354
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Book Description
Author: Robert H. Halstead
Publisher: Springer Science & Business Media
ISBN: 9783540573968
Category : Computers
Languages : en
Pages : 438
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Book Description
Parallel and distributed computing are becoming increasingly important as cost-effective ways to achieve high computational performance. Symbolic computations are notable for their use of irregular data structures and hence parallel symbolic computing has its own distinctive set of technical challenges. The papers in this book are based on presentations made at a workshop at MIT in October 1992. They present results in a wide range of areas including: speculative computation, scheduling techniques, program development tools and environments, programming languages and systems, models of concurrency and distribution, parallel computer architecture, and symbolic applications.
Author: Bo Huang
Publisher: John Wiley & Sons
ISBN: 111961970X
Category : Technology & Engineering
Languages : en
Pages : 288
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Book Description
Presents strategies with reachability graph analysis for optimizing resource allocation systems Supervisory Control and Scheduling of Resource Allocation Systems offers an important guide to Petri net (PN) models and methods for supervisory control and system scheduling of resource allocation systems (RASs). Resource allocation systems are common in automated manufacturing systems, project management systems, cloud data centers, and software engineering systems. The authors—two experts on the topic—present a definition, techniques, models, and state-of-the art applications of supervisory control and scheduling problems. The book introduces the basic concepts and research background on resource allocation systems and Petri nets. The authors then focus on the deadlock-free supervisor synthesis for RASs using Petri nets. The book also investigates the heuristic scheduling of RASs based on timed Petri nets. Conclusions and open problems are provided in the last section of the book. This important book: Includes multiple methods for supervisory control and scheduling with reachability graphs, and provides illustrative examples Reveals how to accelerate the supervisory controller design and system scheduling of RASs based on PN reachability graphs, with optimal or near-optimal results Highlights both solution quality and computational speed in RAS deadlock handling and system scheduling Written for researchers, engineers, scientists, and professionals in system planning and control, engineering, operation, and management, Supervisory Control and Scheduling of Resource Allocation Systems provides an essential guide to the supervisory control and scheduling of resource allocation systems (RASs) using Petri net reachability graphs, which allow for multiple resource acquisitions and flexible routings.
Author: Joseph Kelly Barker
Publisher:
ISBN:
Category :
Languages : en
Pages : 134
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Book Description
Bidirectional heuristic search is a well-known technique for solving pathfinding problems. The goal in a pathfinding problem is to find paths---often of lowest cost---between nodes in a graph. Many real-world problems, such as finding the quickest route between two points in a map or measuring the similarity of DNA sequences, can be modeled as pathfinding problems. Bidirectional brute-force search does simultaneous brute-force searches forward from the initial state and backward from the goal states, finding solutions when both intersect. The idea of adding a heuristic to guide search is an old one, but has not seen widespread use and is generally believed to be ineffective. I present an intuitive explanation for the ineffectiveness of front-to-end bidirectional heuristic search. Previous work has examined this topic, but mine is the first comprehensive explanation for why most front-to-end bidirectional heuristic search algorithms will usually be outperformed by either unidirectional heuristic or bidirectional brute-force searches. However, I also provide a graph wherein bidirectional heuristic search does outperform both other approaches, as well as real-world problem instances from the road navigation domain. These demonstrate that there can be no general, formal proof of the technique's ineffectiveness. I tested my theory in a large number of popular search domains, confirming its predictions. One of my experiments demonstrates that a commonly-repeated explanation for the ineffectiveness of bidirectional heuristic search---that it spends most of its time proving solution optimality---is in fact wrong, and that with a strong heuristic a bidirectional heuristic search tends to find optimal solutions very late in a search. Finally, I introduce state-of-the-art solvers for the four-peg Towers of Hanoi with arbitrary initial and goal states, and peg solitaire, using disk-based, bidirectional algorithms. The Towers of Hanoi solver is a bidirectional brute-force solver which, as my theory predicts, outperforms a unidirectional heuristic solver. The peg solitaire solver is a bidirectional heuristic algorithm with novel heuristics. While my theory demonstrates that bidirectional heuristic search is generally ineffective, the peg solitaire domain demonstrates several caveats to my theory that this algorithm takes advantage of.
