Artificial Intelligence (R0)

This two-volume set LNICST 631 & 632 constitutes the proceedings of the Third Pan-African Conference on Pan-African Intelligence and Smart Systems, PAAISS 2024, which was held in Durban, South Africa, during December 4–6, 2024.

This book is considered as an essential medium to introduce the up-to-date findings, new level research, and developing fields in the area of technology and computing for First International Conference on Emerging Technologies and Computing Innovations (ICETCI-2025). The objective of the ICETCI-2025 is to provide a platform to highlight state-of-the-art research work and innovative findings in technology and computing. The conference is focused on filling the gap between modern theoretical improvements and real-life issues by providing a platform for discussions among experts in different areas concerning innovative fields like AI, ML, big data, blockchain, IoT giant computing, etc. ICETCI-2025 benefits from being a multidisciplinary approach for a broad set of emerging technologies. The conference aims to foster the exchange of ideas and experiences by bringing together leaders, researchers, academics, industry practitioners as well as policymakers. Much of the diversity they provide aids unconventional thinking, applicable implementation, and strategic growth that tackles current as well as future technology hurdles. ICETCI-2025 proceedings present high quality research papers, case studies and reviews focusing on state of the art developments in domains like artificial intelligence, big data analytics, cybersecurity and privacy, IoT and blockchain and cloud computing. By collaborating with academia, industry leaders, and policymakers, these proceedings are essential for bringing attention to emerging trends and best practices. They play a critical role in promoting knowledge, stimulating innovation, and providing cross-disciplinary support to help drive technological development. This book is aimed at researchers, academics, graduate students, industry professionals, and policymakers who have an interest in the field of computing, information technologies, and their application.

Artificial Intelligence: Transcending Traditional Paradigms is a significant new introductory text for undergraduate and graduate course use. It introduces students and professionals to the state-of-the-art development of Artificial Intelligence techniques to develop smart real-world solutions. As an active researcher, the author presents the material authoritatively and with insights that reflect a modern, firsthand understanding of the field.

Artificial intelligence is a science still in its infancy, and that makes it special. It’s not like more established fields, and the author has tried in writing this textbook to honour this characteristic and the ways it makes AI unique.

This book is a comprehensive guide to current practical and theoretical understanding of verification of autonomous systems, helping users find the tools and techniques they need to address this challenging problem. Autonomous systems are transitioning out of the lab and into the commercial and industrial space in ever increasing numbers. Verification provides the assurance case necessary for deployment of autonomous systems, but we lack guidance, certifications, and standards to help a business determine whether their autonomous system is safe, secure, or reliable. A community has formed to develop tools, techniques, and processes to solve this problem, but the existing literature largely focuses on autonomy design tools and techniques rather than on tools and techniques that can be used to verify an existing autonomy design. This book fills that gap. 

It directly connects specific challenges faced by verification agents and autonomy developers with the research and topics most relevant to their concerns:

• Specific challenges faced by stakeholders and researchers are cross-referenced to chapters addressing the relevant tools and techniques.
• Individual aspects of the verification process like requirements and specification development, model tests, and integration tests are mapped into technical challenges related to modeling, testing, abstraction and verification tools.
• Each chapter is tied to both the stakeholder challenges and the technical challenges it addresses.

Verification processes, industrial needs, and issues with verification of learning systems are addressed across all domains, encompassing platforms from aircraft and spacecraft to marine systems and ground vehicles operating in industrial, military, commercial and household applications. Broad in scope, this reference ties advances in formal analysis, hardware testing, verification process modifications, and design and evaluation tools to the needs of verification researchers and professionals.