AI*IA 2005 : Advances in artificial intelligence ; 9th congress of the Italian Association for Artificial Intelligence Milan, Italy, September 21-23, 2005, Proceedings
This volume collects the papers selected for presentation at the IX Congress of the Italian Association for Arti?cial Intelligence (AI*IA), 2005 On the one hand this congress continues the tradition of AI*IA in organizing its biannual s- enti?c meeting from 1989; on the other hand, this edition is a landmark in the involvement of the international community of arti?cial intelligence (AI), directly involving a broad number of experts from several countries in the P- gramCommittee. Moreover,the peculiar nature of scienti?c researchin arti?cial intelligence (which is intrinsically international) and several consolidated int- national collaborations in projects and mobility programs allowed the collection and selection of papers from many di?erent countries, all around the world, enlarging the visibility of the Italian contribution within this research ?eld. Arti?cial intelligence is today a growing complex set of conceptual, theor- ical, methodological, and technological frameworks, o?ering innovative com- tational solutions in the design and development of computer-based systems. Within this perspective, researchers working in this area must tackle a broad range of knowledge about methods, results, and solutions coming from di?erent classical areas of this discipline. The congress was designed as a forum allowing researchers to present and discuss specialized results as general contributions to AI growth.
كتب مشابهة
New challenges in software engineering ; Vol 1
Explores the key challenges shaping the future of software development, including automation, AI-driven development, security-focused engineering, resilient and autonomous architectures, business process optimization, cloud computing, microservices, high-performance distributed systems, and sustainable technologies. Software engineering is undergoing a constant transformation, driven by rapid technological advances and evolving market demands. additionally, it delves into the ethical considerations of AI, the evolution of intuitive user interfaces, and the importance of multidisciplinary collaboration.
Fundamentals of manufacturing engineering using digital visualization
Offers a guide to core principles and practices of manufacturing engineering. It covers the design of, together with technological and measurement issues for, technical systems. Locating charts and setup schemes describing different machining processes are included. Concepts of product quality, with a focus on accuracy indicators, machining accuracy, roughness, and the impact of surface quality on exploitation properties are also explained. Furthermore, key machining methods, including turning, milling, hole machining, grinding, and gear machining, are analyzed in depth, covering their principles, applications, and techniques. The book is enriched by QR codes, linking to a mobile application presenting additional information about the content, for an interactive and extended learning experience. It also uses illustrations visualized with digital tools to promote a better understanding of the concepts.
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
AI in banking : Practical applications and case studies
Delves into the application of AI from theory to practice, offering detailed insights into AI project design and code implementation across eleven business scenarios in four major sectors: retail banking, e-banking, bank credit, and tech operations. it provides hands-on examples of various technologies, including automatic machine learning, integrated learning, graph computation, recommendation systems, causal inference, generative adversarial networks, supervised learning, unsupervised learning, computer vision, reinforcement learning, fuzzy control, automatic control, speech recognition, semantic understanding, bayesian networks, edge computing, and more. this book stands as a rare and practical guide to AI projects in the banking industry.
