Hybrid Offline Online Methods For Optimization Under Uncertainty

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Hybrid Offline/Online Methods for Optimization Under Uncertainty

A. De Filippo
Hybrid Offline Online Methods for Optimization Under Uncertainty Book PDF

Author : A. De Filippo
Publisher : IOS Press
Page : 126 pages
File Size : 42,5 Mb
Release : 2022-04-12
Category : Computers
ISBN : 9781643682631

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Hybrid Offline/Online Methods for Optimization Under Uncertainty by A. De Filippo Pdf

Balancing the solution-quality/time trade-off and optimizing problems which feature offline and online phases can deliver significant improvements in efficiency and budget control. Offline/online integration yields benefits by achieving high quality solutions while reducing online computation time. This book considers multi-stage optimization problems under uncertainty and proposes various methods that have broad applicability. Due to the complexity of the task, the most popular approaches depend on the temporal granularity of the decisions to be made and are, in general, sampling-based methods and heuristics. Long-term strategic decisions that may have a major impact are typically solved using these more accurate, but expensive, sampling-based approaches. Short-term operational decisions often need to be made over multiple steps within a short time frame and are commonly addressed via polynomial-time heuristics, with the more advanced sampling-based methods only being applicable if their computational cost can be carefully managed. Despite being strongly interconnected, these 2 phases are typically solved in isolation. In the first part of the book, general methods based on a tighter integration between the two phases are proposed and their applicability explored, and these may lead to significant improvements. The second part of the book focuses on how to manage the cost/quality trade-off of online stochastic anticipatory algorithms, taking advantage of some offline information. All the methods proposed here provide multiple options to balance the quality/time trade-off in optimization problems that involve offline and online phases, and are suitable for a variety of practical application scenarios.

Integration of Constraint Programming, Artificial Intelligence, and Operations Research

Pierre Schaus
Integration of Constraint Programming Artificial Intelligence and Operations Research Book PDF

Author : Pierre Schaus
Publisher : Springer Nature
Page : 459 pages
File Size : 40,7 Mb
Release : 2022-06-09
Category : Computers
ISBN : 9783031080111

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Integration of Constraint Programming, Artificial Intelligence, and Operations Research by Pierre Schaus Pdf

This book constitutes the proceedings of the 19th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2022, which was held in Los Angeles, CA, USA, in June 2022.The 28 regular papers presented were carefully reviewed and selected from a total of 60 submissions. The conference program included a Master Class on the topic "Bridging the Gap between Machine Learning and Optimization”.

Learning and Reasoning in Hybrid Structured Spaces

P. Morettin
Learning and Reasoning in Hybrid Structured Spaces Book PDF

Author : P. Morettin
Publisher : IOS Press
Page : 112 pages
File Size : 41,6 Mb
Release : 2022-04-15
Category : Computers
ISBN : 9781643682679

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Learning and Reasoning in Hybrid Structured Spaces by P. Morettin Pdf

Artificial intelligence often has to deal with uncertain scenarios, such as a partially observed environment or noisy observations. Traditional probabilistic models, while being very principled approaches in these contexts, are incapable of dealing with both algebraic and logical constraints. Existing hybrid continuous/discrete models are typically limited in expressivity, or do not offer any guarantee on the approximation errors. This book, Learning and Reasoning in Hybrid Structured Spaces, discusses a recent and general formalism called Weighted Model Integration (WMI), which enables probabilistic modeling and inference in hybrid structured domains. WMI-based inference algorithms differ with respect to most alternatives in that probabilities are computed inside a structured support involving both logical and algebraic relationships between variables. While the research in this area is at an early stage, we are witnessing an increasing interest in the study and development of scalable inference procedures and effective learning algorithms in this setting. This book details some of the most impactful contributions in context of WMI-based inference in the last 5 years. Moreover, by providing a gentle introduction to the main concepts related to WMI, the book can be useful for both theoretical researchers and practitioners alike.

Advanced Tools and Methods for Treewidth-Based Problem Solving

M. Hecher
Advanced Tools and Methods for Treewidth Based Problem Solving Book PDF

Author : M. Hecher
Publisher : IOS Press
Page : 252 pages
File Size : 44,6 Mb
Release : 2022-11-15
Category : Computers
ISBN : 9781643683454

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Advanced Tools and Methods for Treewidth-Based Problem Solving by M. Hecher Pdf

This book, Advanced Tools and Methods for Treewidth-Based Problem Solving, contains selected results from the author’s PhD studies, which were carried out from 2015 to 2021. For his PhD thesis, Markus Hecher received the EurAI Dissertation Award 2021 and the GI Dissertation Award 2021, amongst others. The aim of the book is to present a new toolkit for using the structural parameter of treewidth to solve problems in knowledge representation and reasoning (KR) and artificial intelligence (AI), thereby establishing both theoretical upper and lower bounds, as well as methods to deal with treewidth efficiently in practice. The key foundations outlined in the book provide runtime lower bounds – under reasonable assumptions in computational complexity – for evaluating quantified Boolean formulas and logic programs which match the known upper bounds already published in 2004 and 2009. The general nature of the developed tools and techniques means that a wide applicability beyond the selected problems and formalisms tackled in the book is anticipated, and it is hoped that the book will serve as a starting point for future theoretical and practical investigations, which will no doubt establish further results and gain deeper insights.

New Trends in Intelligent Software Methodologies, Tools and Techniques

H. Fujita,Y. Watanobe,T. Azumi
New Trends in Intelligent Software Methodologies Tools and Techniques Book PDF

Author : H. Fujita,Y. Watanobe,T. Azumi
Publisher : IOS Press
Page : 744 pages
File Size : 40,7 Mb
Release : 2022-10-11
Category : Computers
ISBN : 9781643683171

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New Trends in Intelligent Software Methodologies, Tools and Techniques by H. Fujita,Y. Watanobe,T. Azumi Pdf

The integration of applied intelligence with software has been an essential enabler for science and the new economy, creating new possibilities for a more reliable, flexible and robust society. But current software methodologies, tools, and techniques often fall short of expectations, and are not yet sufficiently robust or reliable for a constantly changing and evolving market. This book presents the proceedings of SoMeT_22, the 21st International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, held from 20 - 22 September 2022 in Kitakyushu, Japan. The SoMeT conference provides a platform for the exchange of ideas and experience in the field of software technology, with the emphasis on human-centric software methodologies, end-user development techniques, and emotional reasoning for optimal performance. The 58 papers presented here were each carefully reviewed by 3 or 4 referees for technical soundness, relevance, originality, significance and clarity, they were then revised before being selected by the international reviewing committee. The papers are arranged in 9 chapters: software systems with intelligent design; software systems security and techniques; formal techniques for system software and quality assessment; applied intelligence in software; intelligent decision support systems; cyber-physical systems; knowledge science and intelligent computing; ontology in data and software; and machine learning in systems software. The book assembles the work of scholars from the international research community to capture the essence of the new state-of-the-art in software science and its supporting technology, and will be of interest to all those working in the field.

Exploiting Environment Configurability in Reinforcement Learning

A.M. Metelli
Exploiting Environment Configurability in Reinforcement Learning Book PDF

Author : A.M. Metelli
Publisher : IOS Press
Page : 377 pages
File Size : 48,6 Mb
Release : 2022-12-07
Category : Computers
ISBN : 9781643683638

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Exploiting Environment Configurability in Reinforcement Learning by A.M. Metelli Pdf

In recent decades, Reinforcement Learning (RL) has emerged as an effective approach to address complex control tasks. In a Markov Decision Process (MDP), the framework typically used, the environment is assumed to be a fixed entity that cannot be altered externally. There are, however, several real-world scenarios in which the environment can be modified to a limited extent. This book, Exploiting Environment Configurability in Reinforcement Learning, aims to formalize and study diverse aspects of environment configuration. In a traditional MDP, the agent perceives the state of the environment and performs actions. As a consequence, the environment transitions to a new state and generates a reward signal. The goal of the agent consists of learning a policy, i.e., a prescription of actions that maximize the long-term reward. Although environment configuration arises quite often in real applications, the topic is very little explored in the literature. The contributions in the book are theoretical, algorithmic, and experimental and can be broadly subdivided into three parts. The first part introduces the novel formalism of Configurable Markov Decision Processes (Conf-MDPs) to model the configuration opportunities offered by the environment. The second part of the book focuses on the cooperative Conf-MDP setting and investigates the problem of finding an agent policy and an environment configuration that jointly optimize the long-term reward. The third part addresses two specific applications of the Conf-MDP framework: policy space identification and control frequency adaptation. The book will be of interest to all those using RL as part of their work.

Deep Learning with Relational Logic Representations

G. Šír
Deep Learning with Relational Logic Representations Book PDF

Author : G. Šír
Publisher : IOS Press
Page : 239 pages
File Size : 47,8 Mb
Release : 2022-11-23
Category : Computers
ISBN : 9781643683430

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Deep Learning with Relational Logic Representations by G. Šír Pdf

Deep learning has been used with great success in a number of diverse applications, ranging from image processing to game playing, and the fast progress of this learning paradigm has even been seen as paving the way towards general artificial intelligence. However, the current deep learning models are still principally limited in many ways. This book, ‘Deep Learning with Relational Logic Representations’, addresses the limited expressiveness of the common tensor-based learning representation used in standard deep learning, by generalizing it to relational representations based in mathematical logic. This is the natural formalism for the relational data omnipresent in the interlinked structures of the Internet and relational databases, as well as for the background knowledge often present in the form of relational rules and constraints. These are impossible to properly exploit with standard neural networks, but the book introduces a new declarative deep relational learning framework called Lifted Relational Neural Networks, which generalizes the standard deep learning models into the relational setting by means of a ‘lifting’ paradigm, known from Statistical Relational Learning. The author explains how this approach allows for effective end-to-end deep learning with relational data and knowledge, introduces several enhancements and optimizations to the framework, and demonstrates its expressiveness with various novel deep relational learning concepts, including efficient generalizations of popular contemporary models, such as Graph Neural Networks. Demonstrating the framework across various learning scenarios and benchmarks, including computational efficiency, the book will be of interest to all those interested in the theory and practice of advancing representations of modern deep learning architectures.

Artificial Intelligence Research and Development

A. Cortés,F. Grimaldo,T. Flaminio
Artificial Intelligence Research and Development Book PDF

Author : A. Cortés,F. Grimaldo,T. Flaminio
Publisher : IOS Press
Page : 390 pages
File Size : 46,8 Mb
Release : 2022-11-03
Category : Computers
ISBN : 9781643683270

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Artificial Intelligence Research and Development by A. Cortés,F. Grimaldo,T. Flaminio Pdf

Artificial intelligence has become an integral part of all our lives. Development is rapid in this exciting and far-reaching field, and keeping up to date with the latest research and innovation is crucial to all those working with the technology. This book presents the proceedings of the 24th edition of CCIA, the International Conference of the Catalan Association for Artificial Intelligence, held in Sitges, Spain, from 19 – 21 October 2022. This annual event serves as a meeting point not only for researchers in AI from the Catalan speaking territories (southern France, Catalonia, Valencia, the Balearic Islands and Alghero in Italy) but for researchers from around the world. The programme committee received 59 submissions, from which the 26 long papers and 23 short papers selected for presentation at the conference by the 62 experts who make up the committee are included here. The book is divided into the following sections: combinatorial problem solving and logics for artificial intelligence; sentiment analysis and tekst analysis; data science, recommender systems and decision support systems; machine learning; computer vision; and explainability and argumentation. This book also includes an abstract of the invited talk given by Prof. Fosca Giannotti. Providing a comprehensive overview of research and development, this book will be of interest to all those working in the field of Artificial Intelligence.

ECAI 2020

G. De Giacomo,A. Catala,B. Dilkina
ECAI 2020 Book PDF

Author : G. De Giacomo,A. Catala,B. Dilkina
Publisher : IOS Press
Page : 3122 pages
File Size : 43,5 Mb
Release : 2020-09-11
Category : Computers
ISBN : 9781643681016

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ECAI 2020 by G. De Giacomo,A. Catala,B. Dilkina Pdf

This book presents the proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), held in Santiago de Compostela, Spain, from 29 August to 8 September 2020. The conference was postponed from June, and much of it conducted online due to the COVID-19 restrictions. The conference is one of the principal occasions for researchers and practitioners of AI to meet and discuss the latest trends and challenges in all fields of AI and to demonstrate innovative applications and uses of advanced AI technology. The book also includes the proceedings of the 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) held at the same time. A record number of more than 1,700 submissions was received for ECAI 2020, of which 1,443 were reviewed. Of these, 361 full-papers and 36 highlight papers were accepted (an acceptance rate of 25% for full-papers and 45% for highlight papers). The book is divided into three sections: ECAI full papers; ECAI highlight papers; and PAIS papers. The topics of these papers cover all aspects of AI, including Agent-based and Multi-agent Systems; Computational Intelligence; Constraints and Satisfiability; Games and Virtual Environments; Heuristic Search; Human Aspects in AI; Information Retrieval and Filtering; Knowledge Representation and Reasoning; Machine Learning; Multidisciplinary Topics and Applications; Natural Language Processing; Planning and Scheduling; Robotics; Safe, Explainable, and Trustworthy AI; Semantic Technologies; Uncertainty in AI; and Vision. The book will be of interest to all those whose work involves the use of AI technology.

Modern Management Based on Big Data III

A.J. Tallón-Ballesteros
Modern Management Based on Big Data III Book PDF

Author : A.J. Tallón-Ballesteros
Publisher : IOS Press
Page : 498 pages
File Size : 43,7 Mb
Release : 2022-09-29
Category : Computers
ISBN : 9781643683010

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Modern Management Based on Big Data III by A.J. Tallón-Ballesteros Pdf

Data is the basic ingredient of all Big Data applications, and Big Data technologies are constantly deploying new strategies to maximise efficiency and reduce the time taken to process information. This book presents the proceedings of MMBD2022, the third edition of the conference series Modern Management based on Big Data (MMBD). The conference was originally scheduled to take place from 15 to 18 August 2022 in Seoul, South Korea, but was changed to a virtual event on the same dates. Some 200 submissions were received for presentation at the conference, 52 of which were ultimately accepted after exhaustive review by members of the programme committee and peer-reviewers, who took into account the breadth and depth of the research topics and the scope of MMBD. Topics covered include data analytics, modelling, technologies and visualization, architectures for parallel processing systems, data mining tools and techniques, machine learning algorithms, and big data for engineering applications. There are also papers covering modern management, including topics such as strategy, decision making, manufacturing and logistics-based systems, engineering economy, information systems and law-based information treatment, and papers from a special session covering big data in manufacturing, retail, healthcare, accounting, banking, education, global trading, and e-commerce. Big data analysis and emerging applications were popular topics. The book includes many innovative and original ideas, as well as results of general significance, all supported by clear and rigorous reasoning and compelling evidence and methods, and will be of interest to all those working with Big Data.

PAIS 2022

A. Passerini,T. Schiex
PAIS 2022 Book PDF

Author : A. Passerini,T. Schiex
Publisher : IOS Press
Page : 172 pages
File Size : 44,9 Mb
Release : 2022-08-05
Category : Computers
ISBN : 9781643682952

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PAIS 2022 by A. Passerini,T. Schiex Pdf

Artificial Intelligence (AI) is a central topic in contemporary computer science; one which has enabled many groundbreaking developments that have significantly influenced our society. Not only has it proved to be of fundamental importance in areas such as medicine, biology, economics, philosophy, linguistics, psychology and engineering, but it has also had a significant impact in a number of fields, including e-commerce, tourism, e-government, national security, manufacturing and other economic sectors. This book contains the proceedings of PAIS 2022, the 11th Conference on Prestigious Applications of Artificial Intelligence, held in Vienna, Austria, on 25 July 2022 as a satellite event of IJCAI-ECAI 2022. The PAIS conference invites papers describing innovative applications of AI techniques to real-world systems and problems, and aims to provide a forum for academic and industrial researchers and practitioners to share their experience and insight on the applicability, development and deployment of intelligent systems. A total of 18 full-paper submissions and 4 extended-abstract submissions were received for the 2022 conference, of which 10 full papers and 3 extended abstracts were accepted after rigorous peer review. The topics covered range from autonomous navigation, air traffic control and satellite management to the optimization of industrial processes and human-in-the-loop applications. The book will be of interest to all those whose work involves the innovative application of AI techniques to real-world situations.

Computational Models of Argument

F. Toni,S. Polberg,R. Booth
Computational Models of Argument Book PDF

Author : F. Toni,S. Polberg,R. Booth
Publisher : IOS Press
Page : 400 pages
File Size : 41,5 Mb
Release : 2022-09-29
Category : Computers
ISBN : 9781643683072

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Computational Models of Argument by F. Toni,S. Polberg,R. Booth Pdf

Argumentation has traditionally been studied across a number of fields, notably philosophy, cognitive science, linguistics and jurisprudence. The study of computational models of argumentation is a more recent endeavor, bringing together researchers from traditional fields and computer science and engineering within a rich, interdisciplinary matrix. Computational models of argumentation have been identified and used since the 1980s, and more recently an important role for argumentation in leading to principled decisions has emerged in several settings. This book presents the proceedings of COMMA 2022 the 9th International Conference on Computational Models of Argument, held in Cardiff, Wales, United Kingdom, during 14 - 16 September 2022. The book contains 27 regular papers and 16 demo papers from a total of 75 submissions, as well as 3 invited talks from Prof Paul Dunne (University of Liverpool), Prof Iryna Gurevych (TU Darmstadt), and Prof Antonis Kakas (University of Cyprus), which reflect the diverse nature of the field. Papers are a mix of theoretical and practical contributions; theoretical contributions include new formal models, the study of formal or computational properties of models, design for implemented systems and experimental research; practical papers include applications to law, machine learning and explainability. Abstract and structured accounts of argumentation are covered, as are relations between different accounts. Many papers focus on the evaluation of arguments or their conclusions given a body of arguments, with a continuation of a recent trend to study gradual or probabilistic notions of evaluation. The book offers an overview of recent and current research and will be of interest to all those working with computational models of argumentation.

ECAI 2023

K. Gal,A. Nowé,G.J. Nalepa
ECAI 2023 Book PDF

Author : K. Gal,A. Nowé,G.J. Nalepa
Publisher : IOS Press
Page : 3328 pages
File Size : 54,9 Mb
Release : 2023-10-18
Category : Computers
ISBN : 9781643684376

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ECAI 2023 by K. Gal,A. Nowé,G.J. Nalepa Pdf

Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.

Energy Management—Collective and Computational Intelligence with Theory and Applications

Cengiz Kahraman,Gülgün Kayakutlu
Energy Management Collective and Computational Intelligence with Theory and Applications Book PDF

Author : Cengiz Kahraman,Gülgün Kayakutlu
Publisher : Springer
Page : 554 pages
File Size : 46,7 Mb
Release : 2018-03-21
Category : Technology & Engineering
ISBN : 9783319756905

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Energy Management—Collective and Computational Intelligence with Theory and Applications by Cengiz Kahraman,Gülgün Kayakutlu Pdf

This book presents a selection of recently developed collective and computational intelligence techniques, which it subsequently applies to energy management problems ranging from performance analysis to economic analysis, and from strategic analysis to operational analysis, with didactic numerical examples. As a form of intelligence emerging from the collaboration and competition of individuals, collective and computational intelligence addresses new methodological, theoretical, and practical aspects of complex energy management problems. The book offers an excellent reference guide for practitioners, researchers, lecturers and postgraduate students pursuing research on intelligence in energy management. The contributing authors are recognized researchers in the energy research field.

Route and Operating Optimization of Maritime Vessels Using Machine Learning Techniques

Mohammad Hossein Moradi
Route and Operating Optimization of Maritime Vessels Using Machine Learning Techniques Book PDF

Author : Mohammad Hossein Moradi
Publisher : Logos Verlag Berlin GmbH
Page : 134 pages
File Size : 42,5 Mb
Release : 2024-02-02
Category : Electronic
ISBN : 9783832557720

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Route and Operating Optimization of Maritime Vessels Using Machine Learning Techniques by Mohammad Hossein Moradi Pdf

The shipping industry handles over 90% of the global trade volume and is responsible for approximately 3% of global CO2 emissions. Meanwhile, trade by the shipping industry is expected to increase by up to 130% by 2050 compared to 2008. At the same time, the goal is to reduce Green House Gas (GHG) emissions from the shipping industry to half of the 2008 level by 2050. In support of this goal, this thesis is concerned with a comprehensive approach for optimizing the ship's operation, i.e., an optimization approach that simultaneously involves route selection, energy management, propeller pitch, and engine control. In addition, this thesis also analyses the application of wind propulsion systems. The optimization of the ship's operation is implemented in the form of Reinforcement Learning (RL) methods. The use of RL-based methods to simultaneously optimize various aspects of the ship's trajectory and controls is a novel approach compared to the current state-of-art and embodies this thesis' inherent innovation. The results specifically highlight the importance of parallelizing route optimization with the optimization of other control aspects. Ultimately, it is found that the solution emanating from a purely RL-based approach can be further enhanced when the optimized route, speed, and power profiles are used to perform individual DP-based optimizations on the energy management in a post-processing step.