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ECAI 2023
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 demonstrat...
Advances in Artificial Intelligence
This book constitutes the refereed proceedings of the 29th Canadian Conference on Artificial Intelligence, Canadian AI 2016, held in Victoria, BC, Canada, in May/June 2016. The 12 full papers and 27 short papers presented were carefully reviewed and selected from 97 submissions. The focus of the conference was on the following subjects: actions and behaviours, audio and visual recognition, natural language processing, reasoning and learning, streams and distributed computing.
Integration of AI and OR Techniques in Constraint Programming
This book constitutes the proceedings of the International Conference on the Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming, CPAIOR 2014, held in Cork, Ireland, in May 2014. The 33 papers presented in this volume were carefully reviewed and selected from 70 submissions. The papers focus on constraint programming and global constraints; scheduling modelling; encodings and SAT logistics; MIP; CSP and complexity; parallelism and search; and data mining and machine learning.
Learning and Intelligent Optimization
This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on Learning and Optimization, LION 8, which was held in Gainesville, FL, USA, in February 2014. The 33 contributions presented were carefully reviewed and selected for inclusion in this book. A large variety of topics are covered, such as algorithm configuration; multiobjective optimization; metaheuristics; graphs and networks; logistics and transportation; and biomedical applications.
Using Constraints to Render Websites
Diploma Thesis from the year 2007 in the subject Computer Science - Theory, grade: 1,0, University of Leipzig, language: English, abstract: Constraint programming is an area of Artificial Intelligence which has many applications. This thesis applies its techniques to a new kind of problem - the rendering of online retailer websites. First, in-depth introductions to constraint programming and the problem of rendering a shop website will be given. A prototypical implementation of a constraint problem solver and a system to solve and illustrate the problem will be described. The architecture of the prototypical implementation and specific features, algorithms, and design decisions will be detai...
PAIS 2022
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 ...
ECAI 2012
Artificial intelligence (AI) plays a vital part in the continued development of computer science and informatics. The AI applications employed in fields such as medicine, economics, linguistics, philosophy, psychology and logical analysis, not forgetting industry, are now indispensable for the effective functioning of a multitude of systems. This book presents the papers from the 20th biennial European Conference on Artificial Intelligence, ECAI 2012, held in Montpellier, France, in August 2012. The ECAI conference remains Europe's principal opportunity for researchers and practitioners of Artificial Intelligence to gather and to discuss the latest trends and challenges in all subfields of A...
ECAI 2020
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 ...
Ancient Maya Settlement and the Alacranes Bajo
This work represents the archaeological investigation of a distinctive zone of the Three Rivers Region of northwestern Belize. It contributes to the knowledge of land use by the ancient Maya using excavation, mapping and environmental data, and situates the area within the local, regional and inter-regional context.
Automated Machine Learning
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
