Machine Learning Methods for Planning

Author: Steven Minton

Publisher: Morgan Kaufmann

ISBN: 1483221172

Category: Social Science

Page: 554

View: 552

Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning. Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credit assignment and describe tractable classes of problems for which optimal plans can be derived. This book discusses as well how reactive, integrated systems give rise to new requirements and opportunities for machine learning. The final chapter deals with a method for learning problem decompositions, which is based on an idealized model of efficiency for problem-reduction search. This book is a valuable resource for production managers, planners, scientists, and research workers.

Intelligent Techniques for Planning

Author: Ioannis Vlahavas,Dimitris Vrakas

Publisher: IGI Global

ISBN: 9781591404514

Category: Business & Economics

Page: 364

View: 1373

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.

Artificial Neural Networks and Machine Learning – ICANN 2018

27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings

Author: Věra Kůrková,Yannis Manolopoulos,Barbara Hammer,Lazaros Iliadis,Ilias Maglogiannis

Publisher: Springer

ISBN: 3030014185

Category: Computers

Page: 824

View: 8350

This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning.

Encyclopedia of Machine Learning and Data Mining, Sammut & Webb, 2nd Ed, 2017

Encyclopedia of Machine Learning and Data Mining

Author: Springer Science, Inc

Publisher: Bukupedia


Category: Computers

Page: 1341

View: 7675

Machine learning and data mining are rapidly developing fields. Following the success of the first edition of the Encyclopedia of Machine Learning, we are delighted to bring you this updated and expanded edition. We have expanded the scope, as reflected in the revised title Encyclopedia of Machine Learning and Data Mining, to encompass more of the broader activity that surrounds the machine learning process. This includes new articles in such diverse areas as anomaly detection, online controlled experiments, and record linkage as well as substantial expansion of existing entries such as data preparation. We have also included new entries on key recent developments in core machine learning, such as deep learning. A thorough review has also led to updating of much of the existing content. This substantial tome is the product of an intense effort by many individuals. We thank the Editorial Board and the numerous contributors who have provided the content.We are grateful to the Springer team of Andrew Spencer, Michael Hermann, and Melissa Fearon who have shepherded us through the long process of bringing this second edition to print. We are also grateful to the production staff who have turned the content into its final form. We are confident that this revised encyclopedia will consolidate the first edition’s place as a key reference source for the machine learning and data mining communities.

Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems

Author: Papajorgji, Petraq

Publisher: IGI Global

ISBN: 1466639474

Category: Computers

Page: 252

View: 3804

Many factors can impact large-scale enterprise management systems, and maintaining these systems can be a complicated and challenging process. Therefore, businesses can benefit from an assortment of models and management styles to track and collect data for processes. Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems supplies a wide array of research on the intersections of business modeling, information systems, and optimization techniques. These various business models and structuring methods are proposed to provide ideas, methods, and points of view for managers, practitioners, entrepreneurs, and researchers on how to improve business processes.

Machine Learning: ECML-95

8th European Conference on Machine Learning, Heraclion, Crete, Greece, April 25 - 27, 1995. Proceedings

Author: Nada Lavrač,Stefan Wrobel

Publisher: Springer Science & Business Media

ISBN: 9783540592860

Category: Computers

Page: 370

View: 7150

This volume constitutes the proceedings of the Eighth European Conference on Machine Learning ECML-95, held in Heraclion, Crete in April 1995. Besides four invited papers the volume presents revised versions of 14 long papers and 26 short papers selected from a total of 104 submissions. The papers address all current aspects in the area of machine learning; also logic programming, planning, reasoning, and algorithmic issues are touched upon.

Applications of Learning & Planning Methods

Author: Nikolaos G. Bourbakis

Publisher: World Scientific

ISBN: 9789810205461

Category: Computers

Page: 365

View: 807

Learning and planning are two important topics of artificial intelligence. Learning deals with the algorithmic processes that make a computing machine able to ?learn? and improve its performance during the process of complex tasks. Planning on the other hand, deals with decision and construction processes that make a machine capable of constructing an intelligent plan for the solution of a particular complex problem.This book combines both learning and planning methodologies and their applications in different domains. It is divided into two parts. The first part contains seven chapters on the ongoing research work in symbolic and connectionist learning. The second part includes seven chapters which provide the current research efforts in planning methodologies and their application to robotics.

A Concise Introduction to Models and Methods for Automated Planning

Author: Hector Geffner,Blai Bonet

Publisher: N.A

ISBN: 9781608459698

Category: Computers

Page: 129

View: 9068

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

Machine Learning: ECML 2005

16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings

Author: João Gama,Rui Camacho,Pavel Brazdil,Alípio Jorge,Luís Torgo

Publisher: Springer Science & Business Media

ISBN: 3540292438

Category: Computers

Page: 769

View: 3368

This book constitutes the refereed proceedings of the 16th European Conference on Machine Learning, ECML 2005, jointly held with PKDD 2005 in Porto, Portugal, in October 2005. The 40 revised full papers and 32 revised short papers presented together with abstracts of 6 invited talks were carefully reviewed and selected from 335 papers submitted to ECML and 30 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.

Machine Learning in Radiation Oncology

Theory and Applications

Author: Issam El Naqa,Ruijiang Li,Martin J. Murphy

Publisher: Springer

ISBN: 3319183052

Category: Medical

Page: 336

View: 8528

​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

Statistik-Workshop für Programmierer

Author: Allen B. Downey

Publisher: O'Reilly Germany

ISBN: 3868993436

Category: Computers

Page: 160

View: 2731

Wenn Sie programmieren können, beherrschen Sie bereits Techniken, um aus Daten Wissen zu extrahieren. Diese kompakte Einführung in die Statistik zeigt Ihnen, wie Sie rechnergestützt, anstatt auf mathematischem Weg Datenanalysen mit Python durchführen können. Praktischer Programmier-Workshop statt grauer Theorie: Das Buch führt Sie anhand eines durchgängigen Fallbeispiels durch eine vollständige Datenanalyse -- von der Datensammlung über die Berechnung statistischer Kennwerte und Identifikation von Mustern bis hin zum Testen statistischer Hypothesen. Gleichzeitig werden Sie mit statistischen Verteilungen, den Regeln der Wahrscheinlichkeitsrechnung, Visualisierungsmöglichkeiten und vielen anderen Arbeitstechniken und Konzepten vertraut gemacht. Statistik-Konzepte zum Ausprobieren: Entwickeln Sie über das Schreiben und Testen von Code ein Verständnis für die Grundlagen von Wahrscheinlichkeitsrechnung und Statistik: Überprüfen Sie das Verhalten statistischer Merkmale durch Zufallsexperimente, zum Beispiel indem Sie Stichproben aus unterschiedlichen Verteilungen ziehen. Nutzen Sie Simulationen, um Konzepte zu verstehen, die auf mathematischem Weg nur schwer zugänglich sind. Lernen Sie etwas über Themen, die in Einführungen üblicherweise nicht vermittelt werden, beispielsweise über die Bayessche Schätzung. Nutzen Sie Python zur Bereinigung und Aufbereitung von Rohdaten aus nahezu beliebigen Quellen. Beantworten Sie mit den Mitteln der Inferenzstatistik Fragestellungen zu realen Daten.

Data Analytics for Renewable Energy Integration

Second ECML PKDD Workshop, DARE 2014, Nancy, France, September 19, 2014, Revised Selected Papers

Author: Wei Lee Woon,Zeyar Aung,Stuart Madnick

Publisher: Springer

ISBN: 3319132903

Category: Computers

Page: 151

View: 3019

This book constitutes revised selected papers from the second ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2014, held in Nancy, France, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book.

New Advances in Intelligence and Security Informatics

Author: Wenji Mao,FeiYue Wang

Publisher: Academic Press

ISBN: 0123973244

Category: Computers

Page: 116

View: 3203

The Intelligent Systems Series comprises titles that present state of the art knowledge and the latest advances in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. Traditionally, Intelligence and Security Informatics (ISI) research and applications have focused on information sharing and data mining, social network analysis, infrastructure protection and emergency responses for security informatics. With the continuous advance of IT technologies and the increasing sophistication of national and international security, in recent years, new directions in ISI research and applications have emerged to address complicated problems with advanced technologies. This book provides a comprehensive and interdisciplinary account of the new advances in ISI area along three fundamental dimensions: methodological issues in security informatics; new technological developments to support security-related modeling, detection, analysis and prediction; and applications and integration in interdisciplinary socio-cultural fields. Identifies emerging directions in ISI research and applications that address the research challenges with advanced technologies Provides an integrated account of the new advances in ISI field in three core aspects: methodology, technological developments and applications Benefits researchers as well as security professionals who are involved in cutting-edge research and applications in security informatics and related fields

AI 2003: Advances in Artificial Intelligence

16th Australian Conference on AI, Perth, Australia, December 3-5, 2003, Proceedings

Author: Tamas D. Gedeon,Lance C.C. Fung

Publisher: Springer Science & Business Media

ISBN: 3540206469

Category: Computers

Page: 1075

View: 5265

This book constitutes the refereed proceedings of the 16th Australian Conference on Artificial Intelligence, AI 2003, held in Perth, Australia in December 2003. The 87 revised full papers presented together with 4 keynote papers were carefully reviewed and selected from 179 submissions. The papers are organized in topical sections on ontologies, problem solving, knowledge discovery and data mining, expert systems, neural network applications, belief revision and theorem proving, reasoning and logic, machine learning, AI applications, neural computing, intelligent agents, computer vision, medical applications, machine learning and language, AI and business, soft computing, language understanding, and theory.

Machine Learning

Hands-On for Developers and Technical Professionals

Author: Jason Bell

Publisher: John Wiley & Sons

ISBN: 1118889495

Category: Mathematics

Page: 408

View: 5305

Dig deep into the data with a hands-on guide to machinelearning Machine Learning: Hands-On for Developers and TechnicalProfessionals provides hands-on instruction and fully-codedworking examples for the most common machine learning techniquesused by developers and technical professionals. The book contains abreakdown of each ML variant, explaining how it works and how it isused within certain industries, allowing readers to incorporate thepresented techniques into their own work as they follow along. Acore tenant of machine learning is a strong focus on datapreparation, and a full exploration of the various types oflearning algorithms illustrates how the proper tools can help anydeveloper extract information and insights from existing data. Thebook includes a full complement of Instructor's Materials tofacilitate use in the classroom, making this resource useful forstudents and as a professional reference. At its core, machine learning is a mathematical, algorithm-basedtechnology that forms the basis of historical data mining andmodern big data science. Scientific analysis of big data requires aworking knowledge of machine learning, which forms predictionsbased on known properties learned from training data. MachineLearning is an accessible, comprehensive guide for thenon-mathematician, providing clear guidance that allows readersto: Learn the languages of machine learning including Hadoop,Mahout, and Weka Understand decision trees, Bayesian networks, and artificialneural networks Implement Association Rule, Real Time, and Batch learning Develop a strategic plan for safe, effective, and efficientmachine learning By learning to construct a system that can learn from data,readers can increase their utility across industries. Machinelearning sits at the core of deep dive data analysis andvisualization, which is increasingly in demand as companiesdiscover the goldmine hiding in their existing data. For the techprofessional involved in data science, Machine Learning:Hands-On for Developers and Technical Professionals providesthe skills and techniques required to dig deeper.

Machine Learning: Concepts, Methodologies, Tools and Applications

Concepts, Methodologies, Tools and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

ISBN: 1609608194

Category: Computers

Page: 2124

View: 5256

"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe

Artificial Intelligence for Advanced Problem Solving Techniques

Author: Vlahavas, Ioannis

Publisher: IGI Global

ISBN: 9781599047072

Category: Education

Page: 388

View: 4745

One of the most important functions of artificial intelligence, automated problem solving, consists mainly of the development of software systems designed to find solutions to problems. These systems utilize a search space and algorithms in order to reach a solution. Artificial Intelligence for Advanced Problem Solving Techniques offers scholars and practitioners cutting-edge research on algorithms and techniques such as search, domain independent heuristics, scheduling, constraint satisfaction, optimization, configuration, and planning, and highlights the relationship between the search categories and the various ways a specific application can be modeled and solved using advanced problem solving techniques.