Modeling Decisions for Artificial Intelligence: 19th International Conference, MDAI 2022, Sant Cugat, Spain, August 30 - September 2, 2022, Proceedings

This book presents the refereed proceedings of the 19th International Conference on Modeling Decisions for Artificial Intelligence,MDAI 2022, which explored various aspects of decision processes and presented research in data science, machine learning, data privacy, aggregation functions, human decision-making, graphs, and social networks.

Format: Paperback / softback
Length: 203 pages
Publication date: 27 July 2022
Publisher: Springer International Publishing AG

The 19th International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2022) was held in Sant Cugat, Spain, from August to September 2022, and this book serves as the official proceedings of the conference. The conference received a total of 41 submissions, from which 16 papers were selected for inclusion in this volume. These papers cover a wide range of topics related to decision-making processes, encompassing data science, machine learning, data privacy, aggregation functions, human decision-making, graphs and social networks, and recommendation and search.

The papers are organized into three topical sections: Decision Making and Uncertainty, Data Privacy, and Machine Learning and Data Science.

In the first section, Decision Making and Uncertainty, the papers explore various aspects of decision-making under uncertainty, including decision-making under risk, decision-making with incomplete information, and decision-making with dynamic environments. The authors present novel approaches and algorithms for addressing these challenges, drawing from fields such as probability theory, statistics, and artificial intelligence.

The second section, Data Privacy, focuses on the protection and management of personal data in the age of digitalization. The papers discuss various techniques and technologies for anonymizing, encrypting, and securing data, as well as legal and ethical considerations related to data privacy. The authors explore the challenges and opportunities presented by emerging technologies such as blockchain and artificial intelligence in the context of data privacy.

The third section, Machine Learning and Data Science, explores the intersection of machine learning and data science, with a particular emphasis on developing efficient and effective algorithms for analyzing and extracting valuable insights from large datasets. The papers present novel approaches for machine learning, such as deep learning, natural language processing, and graph learning, and discuss their applications in various domains such as healthcare, finance, and social media.

Overall, this book provides a comprehensive overview of the latest research and developments in the field of Modeling Decisions for Artificial Intelligence, covering a wide range of topics and providing valuable insights for researchers, practitioners, and policymakers alike.

The 19th International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2022) was held in Sant Cugat, Spain, from August to September 2022, and this book serves as the official proceedings of the conference. The conference received a total of 41 submissions, from which 16 papers were selected for inclusion in this volume. These papers cover a wide range of topics related to decision-making processes, encompassing data science, machine learning, data privacy, aggregation functions, human decision-making, graphs and social networks, and recommendation and search.

The papers are organized into three topical sections: Decision Making and Uncertainty, Data Privacy, and Machine Learning and Data Science.

In the first section, Decision Making and Uncertainty, the papers explore various aspects of decision-making under uncertainty, including decision-making under risk, decision-making with incomplete information, and decision-making with dynamic environments. The authors present novel approaches and algorithms for addressing these challenges, drawing from fields such as probability theory, statistics, and artificial intelligence.

The second section, Data Privacy, focuses on the protection and management of personal data in the age of digitalization. The papers discuss various techniques and technologies for anonymizing, encrypting, and securing data, as well as legal and ethical considerations related to data privacy. The authors explore the challenges and opportunities presented by emerging technologies such as blockchain and artificial intelligence in the context of data privacy.

The third section, Machine Learning and Data Science, explores the intersection of machine learning and data science, with a particular emphasis on developing efficient and effective algorithms for analyzing and extracting valuable insights from large datasets. The papers present novel approaches for machine learning, such as deep learning, natural language processing, and graph learning, and discuss their applications in various domains such as healthcare, finance, and social media.

Overall, this book provides a comprehensive overview of the latest research and developments in the field of Modeling Decisions for Artificial Intelligence, covering a wide range of topics and providing valuable insights for researchers, practitioners, and policymakers alike

Weight: 349g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031134470
Edition number: 1st ed. 2022