Adel Ammar – författare

This book presents extensive research on two main problems in robotics: the path planning problem and the multi-robot task allocation problem. It is the first book to provide a comprehensive solution for using these techniques in large-scale environments containing randomly scattered obstacles. The research conducted resulted in tangible results both in theory and in practice. For path planning, new algorithms for large-scale problems are devised and implemented and integrated into the Robot Operating System (ROS). The book also discusses the parallelism advantage of cloud computing techniques to solve the path planning problem, and, for multi-robot task allocation, it addresses the task assignment problem and the multiple traveling salesman problem for mobile robots applications. In addition, four new algorithms have been devised to investigate the cooperation issues with extensive simulations and comparative performance evaluation. The algorithms are implemented and simulated in MATLAB and Webots.

This book provides a comprehensive exploration of the transformative impact of AI technologies across diverse fields. From revolutionizing healthcare diagnostics and advancing natural language processing for low-resource languages to enhancing software development and promoting environmental sustainability, this book explores the cutting-edge advancements and practical applications of generative AI and large language models (LLMs). With a focus on both opportunities and challenges, the book examines the architectural challenges of transformer-based models, the ethical implications of AI, and the importance of language-specific adaptations, particularly for low-resource languages like Arabic. It also highlights the role of AI in code development, multimodal applications, and its integration with intellectual property frameworks. This book is an essential resource for researchers, practitioners, and policymakers seeking to understand and harness the potential of AI to drive innovation and global progress.

This book provides a comprehensive exploration of the transformative impact of AI technologies across diverse fields. From revolutionizing healthcare diagnostics and advancing natural language processing for low-resource languages to enhancing software development and promoting environmental sustainability, this book explores the cutting-edge advancements and practical applications of generative AI and large language models (LLMs). With a focus on both opportunities and challenges, the book examines the architectural challenges of transformer-based models, the ethical implications of AI, and the importance of language-specific adaptations, particularly for low-resource languages like Arabic. It also highlights the role of AI in code development, multimodal applications, and its integration with intellectual property frameworks. This book is an essential resource for researchers, practitioners, and policymakers seeking to understand and harness the potential of AI to drive innovation and global progress.

Artificial Intelligence is transitioning from passive predictive models to Agentic AI—systems capable of autonomous reasoning, goal-directed behavior, and dynamic interaction with complex environments. This book provides a comprehensive examination of this paradigm, integrating conceptual foundations with architectural frameworks and diverse real-world applications. It clarifies key definitions of agency, critically analyzes agent capabilities and limitations, and details the core mechanics of autonomous reasoning that distinguish agentic systems from traditional automation.The book surveys emerging methodologies, including the evolution from Retrieval-Augmented Generation (RAG) to Agentic RAG, multimodal curiosity mechanisms in language models, and hybrid LLM–optimizer approaches for complex scheduling and orchestration. It further bridges theory and practice through domain-specific chapters addressing deployment in healthcare—emphasizing explainable interpretation for EEG-based classification—enterprise BPM and workflow-centric systems, and cyber-physical infrastructures. Technical contributions also examine tool-based multi-agent engineering workflows, such as automated CAD-to-mesh transformation. Concluding with a critical assessment of challenges and opportunities, the volume offers a rigorous reference for researchers and practitioners advancing autonomous intelligent systems.

This book propels the conversation from static models to autonomous, agentic systems. As AI transitions from a tool for generation to a platform for action, this book offers a critical roadmap for the next frontier: Agentic AI.At the heart of this book is the concept of “Agent Operating Systems,” a revolutionary architecture designed to govern, secure, and scale autonomous agents. This book explores the engineering behind these systems, delving into Agentic Cybersecurity Systems and the architectural trade-offs required for billions of interacting agents.Beyond foundational systems, this book bridges modalities in Multimodal Generative Intelligence, showcasing the synergy between LLMs, GANs, and neuromorphic computing to create responsive, multimodal avatars. A dedicated section on AI for Healthcare presents culturally adaptive tools for the MENA region and advanced Agentic Graph Reasoning for dermatological diagnosis, where self-correcting agents leverage Knowledge Graphs to ensure explainability.Real-world applications continue in Applied Generative AI, where the book covers the optimization of Retrieval-Augmented Generation (RAG) systems, the evolution of geometric intelligence in CAD and Meshes, and intelligent chatbot-assisted software testing.This book is essential reading for researchers and engineers building the future of intelligence—where AI not only speaks but acts.Prof. Anis Koubaa, Prof. Adel Ammar, Prof. Wadii Boulila, Prof. Lahouari Ghouti, Prof. Bilel BenjdiraEditorsAlfaisal University, Riyadh, Saudi ArabiaFebruary 2026

This book presents extensive research on two main problems in robotics: the path planning problem and the multi-robot task allocation problem. It is the first book to provide a comprehensive solution for using these techniques in large-scale environments containing randomly scattered obstacles. The research conducted resulted in tangible results both in theory and in practice. For path planning, new algorithms for large-scale problems are devised and implemented and integrated into the Robot Operating System (ROS). The book also discusses the parallelism advantage of cloud computing techniques to solve the path planning problem, and, for multi-robot task allocation, it addresses the task assignment problem and the multiple traveling salesman problem for mobile robots applications. In addition, four new algorithms have been devised to investigate the cooperation issues with extensive simulations and comparative performance evaluation. The algorithms are implemented and simulated in MATLAB and Webots.