Distributed AI in the Modern World
Technical and Social Aspects of Interacting Intelligent Agents
- 1st Edition - May 1, 2026
- Latest edition
- Editors: Andrei Olaru, Luis Gustavo Nardin, Alexandru Sorici, Adina Magda Florea
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 4 4 6 7 9 - 5
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 4 4 6 8 0 - 1
Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents several state-of-the-art insights into the various forms of distri… Read more
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Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents several state-of-the-art insights into the various forms of distribution of artificial intelligence, with practical application instances. This book does not analyze the internal workings of machine learning models (for instance, in the case of multi-agent reinforcement learning), but instead provides readers with an overview of the challenges brought by the need of artificially intelligent entities to interact with other entities and with their environment along with practical solutions at an architectural level. Deployment, maintenance and monitoring of distributed machine learning systems brings about many practical challenges, dealing with the intelligent agents distributed across a network of heterogenous devices, or interacting with robots and humans alike. While these scenarios are very different, some challenges remain the same when interaction exists: discoverability, availability, communication language and formats, and efficiency in transferring significant amounts of information. The book provides readers with practical solutions at an architectural level, with solutions presented in three parts. Part 1 deals with the distribution of the learning process and the utilization of machine learning models in a distributed system. Part 2 deals with tools that enable the distribution and interaction of artificial learning entities and how multi-agent systems and machine learning can be combined. Part 3 deals with the physical embodiment of intelligent agents and the interaction of intelligent computing units bound to physical space. The three parts are followed by a conclusion, emphasizing the challenges that are common to all scenarios and solutions which apply in a wider range of cases.
- Presents leading-edge insights on the diverse ways artificial intelligence is distributed, along with real-world application examples
- Offers readers a summary of the challenges posed by the necessity for artificially intelligent entities to engage with other entities and their surroundings and proposes practical architectural-level solutions
- Explores communication in local networks, on the web, and within physical environments
- Examines machine learning distributed across a network, into software agents using machine learning models to make decisions, into agents working on the web and in socio-technical networks, and in AI embodied in robots
Computer Science researchers, artificial intelligence researchers, and researchers and practitioners working in the fields of data science, machine learning, and optimization. The primary audience also includes data analysts and software engineers, as well as academics and researchers whose work intersects the field of distributed artificial intelligence, with a focus on interaction
Part 1. Models and applications of distributed machine learning
1. Federated learning solutions and applications
2. Distributed multi-agent learning
3. Models for machine learning on the edge of the network
4. Sharing knowledge about machine learning models in a community of agents
Part 2. Infrastructures for distributed AI
5. Integration of machine learning models in agent-based applications
6. Frameworks for organizing heterogeneous entities and resources in complex scenarios
7. Adaptive interaction across heterogeneous electronic environments
Part 3. Agents in the real-world
8. Interaction in swarms of physically deployed robots
9. Interaction in social humanoid robots
10. Socio-technical networks and hyperagents
11. Web of things and autonomous agents
1. Federated learning solutions and applications
2. Distributed multi-agent learning
3. Models for machine learning on the edge of the network
4. Sharing knowledge about machine learning models in a community of agents
Part 2. Infrastructures for distributed AI
5. Integration of machine learning models in agent-based applications
6. Frameworks for organizing heterogeneous entities and resources in complex scenarios
7. Adaptive interaction across heterogeneous electronic environments
Part 3. Agents in the real-world
8. Interaction in swarms of physically deployed robots
9. Interaction in social humanoid robots
10. Socio-technical networks and hyperagents
11. Web of things and autonomous agents
- Edition: 1
- Latest edition
- Published: May 1, 2026
- Language: English
AO
Andrei Olaru
Dr. Andrei Olaru is an Associate Professor with the National University of Science and Technology POLITEHNICA Bucharest (UNSTPB), and a member of the Artificial Intelligence and Multi-agent Systems Laboratory, specialized in multi-agent systems, ambient intelligence, and context-awareness. He has received a double M.Sc. Degree from University Politehnica of Bucharest (UPB, now UNSTPB) and from University of Nantes, and a double Ph.D. Degree from UPB and University Pierre et Marie Curie (now Sorbonne University). Among other subjects, he teaches a course on Multi-Agent Systems to master students at UNSTPB. He is the coordinator of the Financial Computing Master's Degree at UNSTPB. Dr. Olaru has been the director of 2 national research grants and 1 international grant. He is a member of ACM and a member of the Romanian Association for Artificial Intelligence.
Affiliations and expertise
Department of Computer Science, National University of Science and Technology Politehnica, Bucharest, RomaniaLN
Luis Gustavo Nardin
Dr. Luis Gustavo Nardin is an associate professor in the Department of Computer Science and Intelligent Systems at IMT Mines Saint-Étienne (MSE) and a member of the Laboratory of Informatics, Modelling and Optimization of the Systems (LIMOS UMR 6158). He holds a M.Sc. (2009) and Ph.D. (2015) degrees in Electrical Engineering with specialization in Artificial Intelligence from the University of São Paulo, Brazil. He teaches multi-agent system (MAS), software engineering, and cloud computing courses to the undergraduate students and the Cyber-Physical and Social Systems (CPS2) master students at MSE. His main research interests are models, tools, and methodologies for the regulation of MAS. He also conducts research on agent-based simulation focused on understanding the impacts of social and human behaviors and institutional policies on the emergent properties of complex adaptive systems. Dr. Nardin has previously held faculty positions in the School of Computing at the National College of Ireland and the Brandenburg University of Technology in Cottbus, Germany, after spending some time in a Postdoctoral Fellowship position at the Center for Modeling Complex Interactions at the University of Idaho, USA. Dr. Nardin is the coordinator of the international project ANR-FAPESP Normative Artificial Intelligence for Regulating Manufacturing (NAIMAN) in collaboration with the University of São Paulo, developing normative models and mechanisms for regulating the manufacturing industry. He also leads the organization of the Summer School on AI Technologies for Trust, Interoperability, Autonomy and Resilience in Industry 4.0 (AI4Industry) in collaboration with a broad range of academic institutions and industrial partners. He participates in the ANR-SNF HyperAgents project in developing regulation ontologies and mechanisms for supporting the deployment of world-wide hybrid communities of people and artificial agents on the Web, and in the ANR ACCELER-AI project at developing models and mechanisms for the multi-faceted bounding of the learning of ethical behavior.
Affiliations and expertise
Department of Computer Science and Intelligent Systems, IMT Mines Saint-Étienne, FranceAS
Alexandru Sorici
Dr. Alexandru Sorici is a Lecturer in the Department of Computer Science, National University of Science and Technology POLITEHNICA and a member of the AI-MAS Laboratory. Dr. Sorici holds a Ph.D. in Computer Science from UPB and École Nationale Supérieure des Mines de Saint-Étienne. His research interests encompass context management, agent-oriented programming, human activity recognition, and ambient intelligence (which extends to research in assisted robotics, autonomous driving, and wearable device data analysis in a medical context). Currently, Dr. Sorici is leading the postdoc project CASHMERE, where he works on developing services that ensure dynamic context-dependent authorization for the discovery and use of web resources by software agents in hypermedia agent systems. Dr. Sorici is also a member of the HORIZON 2020 ALAMEDA project, which focuses on studying the predictive power of data from wearable devices and patient logs in determining the health status of patients suffering from neurological diseases such as Multiple Sclerosis, Parkinson's, and stroke recovery. Within the project he is responsible for the management of the patient data collection protocol and interfacing between the medical and technical teams. Dr. Sorici serves as the Secretary of the Romanian Association for Artificial Intelligence (ARIA). In this role, he has contributed to organizing several events aimed at education and raising public awareness about Artificial Intelligence.
Affiliations and expertise
Department of Computer Science, National University of Science and Technology POLITEHNICA, Bucharest, RomaniaAF
Adina Magda Florea
Dr. Adina Magda Florea is Professor in the Department of Computer Science of the National University of Science and Technology POLITEHNICA Bucharest and is the Director of the International Center of Excellence in Artificial Intelligence of the university. Her research interests are in multi-agent systems, machine learning, ambient intelligence, active and assisted living, social robots, and human-robot interaction. Dr. Florea founded and holds the chair of Artificial Intelligence at UNSTPB, was the director of over 25 national RDI grants and 6 international grants and coordinated the development of the PRECIS Research Center. Dr. Florea has been an invited professor at several European universities and had a one-year invited professorship at Worcester Polytechnic Institute, MA, USA. She is Senior Member of IEEE, Senior Member of ACM, President of the Romanian Association for Artificial Intelligence, and Chair of IEEE Romanian Section Chapter of Computational Intelligence.
Affiliations and expertise
Department of Computer Science, National University of Science and Technology POLITEHNICA, Bucharest, Romania