Socionics : Scalability of complex social systems
Includes contributions from an interdisciplinary field of research we call Socionics. Based on a close cooperation between sociologists and researchers from distributed artificial intelligence and multiagent systems, Socionics deals with the exploration of the emergence and dynamics of artificial social systems, agent societies, as well as hybrid man-machine societies. The aim is both to develop intelligent computer technologies by picking up theoretical concepts and methods from sociology and to improve sociological models of societies and organizations by using advanced computer technology. The 15 articles in this state-of-the-art survey combine selected contributions from sociology and informatics on the modeling, construction, and study of complex social systems with special regard to the problem of scaling multiagent systems. The discussion focuses on four specific research areas: multi-layer modeling, organization and self-organization, emergence of social structures, and paths from an agent-centered to a communication-centered perspective in modeling multiagent systems.
كتب مشابهة
Scalable data management for future hardware
Presents the results of the DFG priority program on scalable data management for future hardware. It details requirements and solutions of how modern and future hardware architectures can be leveraged to address the challenges in modern data management.the nine chapters of the book present a wide range of data management architectures in conjunction with current hardware developments, often related to applications in data analytics or machine learning. they cover topics such as hardware-accelerated query or event processing on FPGA, GPU, and multicore CPUs, scalable data management in data center networks or on modern memory and storage technologies, and operating system support.
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.
