Agentic AI and Autonomous Systems: Architectures, Collaboration, and Applications

Expected date of publication: December 2026

Pages: 200

Edited by: Vijayan Sugumaran (Oakland University, USA) and Brij B. Gupta (Asia University, Taiwan)

ISBN: To be assigned

Agentic AI and Autonomous Systems: Architectures, Collaboration, and Applications presents a comprehensive exploration of the emerging paradigm of Agentic Artificial Intelligence (AI), focusing on the design, development, coordination, and deployment of intelligent autonomous systems that can reason, plan, make decisions, and interact with dynamic environments.

Unlike conventional AI systems that primarily respond to predefined instructions or perform isolated predictive tasks, Agentic AI introduces autonomous and goal-directed capabilities that enable intelligent agents to perceive their surroundings, formulate strategies, execute actions, collaborate with other agents, and adapt to changing conditions with varying degrees of human supervision.

This book brings together fundamental concepts, advanced architectures, enabling technologies, and practical applications of Agentic AI and autonomous systems. It examines how to integrate large language models (LLMs), foundation models, reinforcement learning, knowledge representation, memory mechanisms, planning algorithms, and tool-augmented reasoning to develop adaptive, intelligent agent-based solutions.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Agentic AI architectures and frameworks.
Large language and foundation models for autonomous agents.
Reasoning, planning, memory, and decision-making.
Multi-agent communication and collaboration.
Reinforcement learning and adaptive agents.
Agentic workflows and human–AI collaboration.
Trustworthy, explainable, and secure agentic AI.
Agentic AI for cybersecurity and threat management.
Multi-agent intelligence for IoT and smart networks.
Agentic AI in healthcare, robotics, and industry.
Emerging challenges and future research directions.

Keywords: Agentic AI, Autonomous Systems, Intelligent Agents, Multi-Agent Systems, LLMs, Foundation Models, Autonomous Decisions, Agent Collaboration

Table of Contents:

Coming soon.

Readership: Researchers, academics, postgraduate students, and industry professionals working in AI, autonomous and multi-agent systems, robotics, cybersecurity, and IoT.

Vijayan Sugumaran

Oakland University, USA

Vijayan Sugumaran is Distinguished University Professor and Janke Scholar of Management Information Systems at Oakland University, where he chairs the Department of Decision and Information Sciences, co-directs the Institute for Data Science, and directs the Master of Science in Business Analytics. He joined the faculty in 1999, became a professor in 2007, and was named Distinguished Professor in 2020. He received his Ph.D. in information technology from George Mason University. His research covers big data management and analytics, ontologies and the semantic web, and intelligent and multi-agent systems. He has published more than 350 peer-reviewed articles and has edited twenty books, with work in Information Systems Research, ACM Transactions on Database Systems, Communications of the ACM, and several IEEE transactions.

He is editor-in-chief of the International Journal of Intelligent Information Technologies and the Journal of Web Engineering, and he serves on the editorial boards of eight journals. He is co-principal investigator on a $2 million National Science Foundation grant (2023–2028) to train students in data science and entrepreneurship, and he has also held grants from the Korea Research Foundation and the Research Grants Council of Hong Kong. In 2025 SAS named him a SAS Educator for leadership in data and artificial-intelligence education; student teams he guided won the energy track of the SAS Hackathon in 2024 and the forecasting track in 2023. He received Oakland University’s Research Excellence Award in 2010, was a Fulbright Specialist in 2012, and was a visiting professor at Sogang University in Seoul and an international expert at Shanghai University. He has chaired the Intelligent Agent and Multi-Agent Systems track at the Americas Conference on Information Systems since 1999 and has been program chair of conferences including NLDB, ACIS, and the IEEE International Conference on Big Data Service and Applications.

Brij B. Gupta

Asia University, Taiwan

Brij B. Gupta (Senior Member, IEEE) is a distinguished professor in the Department of Computer Science and Information Engineering and the director of the International Center for AI and Cyber Security Research and Innovations (CCRI) at Asia University, Taiwan. He also serves as an adjunct professor at the University of Ottawa, Canada, and Korea University, South Korea. Professor Gupta has a PhD in computer science and engineering and over 20 years of academic and research experience. He has authored more than 500 high-quality research papers, over 35 books, and holds multiple patents. He is recognized globally for his outstanding research contributions, and since 2020, he has been consistently ranked among the top 2% of scientists worldwide by Stanford University and Elsevier. He is also a Clarivate Highly Cited Researcher (top 1%) in computer science, reflecting his exceptional research impact.

Professor Gupta has received numerous prestigious national and international awards, including the Canadian Commonwealth Scholarship, Faculty Research Fellowship Award, IEEE GCCE Outstanding Paper Award, and multiple Best Paper and Best Faculty Awards. He actively contributes to the global research community through editorial leadership roles, serving as editor-in-chief and editorial board member for several high-impact international journals. He has also served as a Distinguished Lecturer of the IEEE Consumer Technology Society and as a Member-at-Large on its Board of Governors, along with key roles in organizing and chairing numerous top-tier IEEE conferences.

His research spans artificial intelligence, cybersecurity, blockchain technologies, cloud and edge computing, intrusion detection systems, cyber-physical systems, and social network analysis. He has been actively involved in international collaborations, interdisciplinary research, and mentoring students and researchers at the undergraduate, postgraduate, and doctoral levels.

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