Front-to-end Bidirectional Heuristic Search

Front-to-end Bidirectional Heuristic Search PDF 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.

Front-to-end Bidirectional Heuristic Search

Front-to-end Bidirectional Heuristic Search PDF 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.

Bidirectional Heuristic Search

Bidirectional Heuristic Search PDF Author: George Politowski
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 160

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Book Description


Revisiting the Theory and Practice of Bidirectional and Suboptimal Heuristic Search Algorithms

Revisiting the Theory and Practice of Bidirectional and Suboptimal Heuristic Search Algorithms PDF Author: Jingwei Chen
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 0

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Book Description
Heuristic Search is a general problem-solving method widely used in artificial intelligence (AI). This thesis presents contributions to heuristic search, including contributions to bidirectional optimal search and unidirectional suboptimal search. For bidirectional optimal search, this thesis presents fundamental theory for the analysis of necessary expansions and the minimum possible number of node expansions needed to solve a given problem in front-to-end heuristic search. A new front-to-end heuristic search algorithm, NBS, which has a worst case guarantee for the number of node expansions, is also presented in this thesis. For unidirectional suboptimal search, this thesis presents the theory of best-first bounded-suboptimal search using priority functions that do not need to perform state re-expansions as long as the search heuristic is consistent. Also, particular priority functions, such as piecewise linear functions are presented in this document. Several new priority functions can significantly outperform existing approaches according to empirical results.

Heuristic Search

Heuristic Search PDF 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

STAIRS 2012

STAIRS 2012 PDF Author: Kristian Kersting
Publisher: IOS Press
ISBN: 1614990956
Category : Computers
Languages : en
Pages : 376

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Book Description
The field of Artificial Intelligence is one in which novel ideas and new and original perspectives are of more than usual importance. The Starting AI Researchers' Symposium (STAIRS) is an international meeting which supports AI researchers from all countries at the beginning of their career, PhD students and those who have held a PhD for less than one year. It offers doctoral students and young post-doctoral AI fellows a unique and valuable opportunity to gain experience in presenting their work in a supportive scientific environment, where they can obtain constructive feedback on the technical content of their work, as well as advice on how to present it, and where they can also establish contacts with the broader European AI research community.This book presents revised versions of peer-reviewed papers presented at the Sixth STAIRS, which took place in Montpellier, France, in conjunction with the 20th European Conference on Artificial Intelligence (ECAI) and the Seventh Conference on Prestigious Applications of Intelligent Systems (PAIS) in August 2012.The topics covered in the book range over a broad spectrum of subjects in the field of AI: machine learning and data mining, constraint satisfaction problems and belief propagation, logic and reasoning, dialogue and multiagent systems, and games and planning. Offering a fascinating opportunity to glimpse the current work of the AI researchers of the future, this book will be of interest to anyone whose work involves the use of artificial intelligence and intelligent systems.

ECAI 2004

ECAI 2004 PDF Author: Ramon López de Mántaras
Publisher: IOS Press
ISBN: 9781586034528
Category : Artificial intelligence
Languages : en
Pages : 1184

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Book Description
This is the Golden Age for Artificial Intelligence. The world is becoming increasingly automated and wired together. This also increases the opportunities for AI to help people and commerce. Almost every sub field of AI had now been used in substantial applications. Some of the fields highlighted in this publication are: CBR Technology; Model Based Systems; Data Mining and Natural Language Techniques. Not only does this publication show the activities, capabilities and accomplishments of the sub fields, it also focuses on what is happening across the field as a whole.

IJCAI-99

IJCAI-99 PDF Author: Thomas L. Dean
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 812

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Book Description


Artificial Intelligence and Mobile Services – AIMS 2019

Artificial Intelligence and Mobile Services – AIMS 2019 PDF Author: De Wang
Publisher: Springer
ISBN: 3030233677
Category : Computers
Languages : en
Pages : 189

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Book Description
This book constitutes the proceedings of the 8th International Conference on Artificial Intelligence and Mobile Services, AIMS 2019, held as part of SCF 2019, in San Diego, CA, USA, in June 2019. The 12 full papers and one short paper presented were carefully reviewed and selected from 29 submissions. The papers cover different aspects of mobile services from business management to computing systems, algorithms and applications. They promote technological technological innovations in research and development of mobile services, including, but not limited to, wireless and sensor networks, mobile and wearable computing, mobile enterprise and eCommerce, ubiquitous collaborative and social services, machine-to-machine and Internet-of-things, clouds, cyber-physical integration, and big data analytics for mobility-enabled services.

Explorations in Bidirectional Heuristic Search

Explorations in Bidirectional Heuristic Search PDF Author: Randy Beth Pollack
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 142

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Book Description


Artificial Intelligence in the 21st Century

Artificial Intelligence in the 21st Century PDF Author: Stephen Lucci
Publisher: Mercury Learning and Information
ISBN: 1944534539
Category : Computers
Languages : en
Pages : 1168

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Book Description
This new edition provides a comprehensive, colorful, up-to-date, and accessible presentation of AI without sacrificing theoretical foundations. It includes numerous examples, applications, full color images, and human interest boxes to enhance student interest. New chapters on robotics and machine learning are now included. Advanced topics cover neural nets, genetic algorithms, natural language processing, planning, and complex board games. A companion DVD is provided with resources, applications, and figures from the book. Numerous instructors’ resources are available upon adoption. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. FEATURES: • Includes new chapters on robotics and machine learning and new sections on speech understanding and metaphor in NLP • Provides a comprehensive, colorful, up to date, and accessible presentation of AI without sacrificing theoretical foundations • Uses numerous examples, applications, full color images, and human interest boxes to enhance student interest • Introduces important AI concepts e.g., robotics, use in video games, neural nets, machine learning, and more thorough practical applications • Features over 300 figures and color images with worked problems detailing AI methods and solutions to selected exercises • Includes DVD with resources, simulations, and figures from the book • Provides numerous instructors’ resources, including: solutions to exercises, Microsoft PP slides, etc.