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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....
In recent years, interest within the research community and the legal industry regarding technological advances in legal knowledge representation and processing has been growing. This relates to areas such as computational models of legal reasoning, cybersecurity,...
Machine learning (ML) and artificial intelligence (AI) applications are now so pervasive that they have become indispensable facilitators which improve the quality of all our daily lives. This book presents the proceeding of MLIS 2022, the 4th International Conference...
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...
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...
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...
Fuzzy logic is vital to applications in the electrical, industrial, chemical and engineering realms, as well as in areas of management and environmental issues. Data mining is indispensible in dealing with big data, massive data, and scalable, parallel and distributed...
Recent developments in parallel computing for various fields of application are providing improved solutions for handling data. These newer, innovative ideas offer the technical support necessary to enhance intellectual decisions, while also dealing more efficiently...
One of the core problems in artificial intelligence is the modelling of human reasoning and intelligent behaviour. The representation of knowledge, and reasoning about it, are of crucial importance in achieving this. This book, Semantics of Belief Change Operators for...
Although cybersecurity is something of a latecomer on the computer science and engineering scene, there are now inclinations to consider cybersecurity a meta-discipline. Unlike traditional information and communication systems, the priority goal of the cybersecurity of...
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...
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...
Semantic systems lie at the heart of modern computing, interlinking with areas as diverse as AI, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence,...
Data is the basic ingredient of all BigData applications, and BigData 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...
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,...
The term Intelligent Environments (IEs) refers to physical spaces in which information and communication technologies are interwoven with sensing technologies, innovative user interfaces, robotics and artificial intelligence to create interactive spaces which increase...
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...
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...
The technologies applied in design studies vary from basic theories to more application-based systems, and intelligence engineering technologies – such as computer-aided industrial design, human factor design, and greenhouse design – play a significant role in design...
Knowledge graphs are increasingly used in scientific and industrial applications. The large number and size of knowledge graphs published as Linked Data in autonomous sources has led to the development of various interfaces to query these knowledge graphs. Therefore,...
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