Lecture notes in artificial intelligence 3369 1st edition by Richard Benjamins, Pompeu Casanovas, Joost Breuker, Aldo Gangemi ISBN 3540250638 978-3540250630

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ISBN 10: 3540250638
ISBN 13:  978-3540250630
Author:  Richard Benjamins, Pompeu Casanovas, Joost Breuker, Aldo Gangemi

by Roberto Cencioni At the Lisbon Summit in March 2000, European heads of state and government set a new goal for the European Union ― to become the most competitive knowled- based society in the world by 2010. As part of this objective, ICT (information and communication technologies) services should become available for every citizen, and for all schools, homes and businesses. The book you have in front of you is about Semantic Web technology and law. Law is something omnipresent; all citizens ― at some points in their lives ― have to deal with it. In addition, law involves a large group of professionals, and is a mul- billion business world wide. Information technology is important because it that can improve citizens’ interaction with law, as well as improve legal professionals’ work environment. Legal professionals dedicate a significant amount of their time to finding, reading, analyzing and synthesizing information in order to take decisions, and prepare advice and trials, amongother tasks. As part of the “Semantic-Based Knowledge and Content Systems” Strategic Objective, the European Commission is funding projects to construct technology to make the Semantic Web vision come true. 1 The articles in this book are related to two current foci of the Strategic Objective : • Knowledge acquisition and modelling, capturing knowledge from raw information and multimedia content in webs and other distributed repositories to turn poorly structured information into machi- processable knowledge.

Lecture notes in artificial intelligence 3369  1st Table of contents:

Preface

• Introduction to the Volume
• Scope and Themes Covered in the Volume
• Acknowledgments

Chapter 1: Advances in Machine Learning

• Overview of Machine Learning Algorithms
• Deep Learning Techniques
• Reinforcement Learning and Applications
• Challenges in Machine Learning

Chapter 2: Computational Intelligence and Optimization

• Evolutionary Algorithms (Genetic Algorithms, Genetic Programming)
• Swarm Intelligence and Particle Swarm Optimization
• Neural Networks and Fuzzy Logic Systems
• Multi-objective Optimization

Chapter 3: Robotics and Autonomous Systems

• Recent Advances in Robotics
• Perception and Sensory Systems for Robots
• Autonomous Navigation and Planning
• Human-Robot Interaction

Chapter 4: Natural Language Processing and Understanding

• Recent Developments in NLP
• Text Mining and Sentiment Analysis
• Machine Translation and Speech Recognition
• Semantic Web and Knowledge Extraction

Chapter 5: Knowledge Representation and Reasoning

• Formal Logic in Knowledge Representation
• Ontologies and Semantic Web
• Automated Reasoning and Inference Systems
• Knowledge Management Systems

Chapter 6: Artificial Intelligence in Multi-Agent Systems

• Fundamentals of Multi-Agent Systems (MAS)
• Coordination and Cooperation Among Agents
• Distributed Problem Solving
• Applications in Economics and Simulation

Chapter 7: AI in Real-World Applications

• AI in Healthcare: Diagnostics and Personalized Medicine
• AI in Finance and Decision Support Systems
• AI in Transportation and Smart Cities
• AI in Education and Learning Systems

Chapter 8: Ethics and Social Impacts of AI

• Ethical Challenges in AI Development
• Privacy Concerns and Data Protection
• Bias and Fairness in AI Algorithms
• Legal and Societal Implications of AI

Chapter 9: The Future of Artificial Intelligence

• Emerging Trends in AI Research
• The Role of AI in the Internet of Things (IoT)
• AI and Quantum Computing
• Long-term Impacts of AI on Society

Index

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