Generative-AI learning systems typically centralize conversational information in one agent or use multiple agents primarily as tutors or collaborators. This study presents a distributed multi-agent generative-AI architecture in which role-specific A...
Radiology is undergoing a paradigm shift from traditional single-function AI systems to sophisticated multi-agent networks capable of autonomous reasoning, coordinated decision-making, and adaptive workflow management. These agentic AI systems move b...
Modern power systems are undergoing a structural transformation driven by the rapid integration of renewable energy sources, distributed energy resources, electrification, and increasing operational uncertainty. These developments expose the limitati...
This study investigates the implementation of LLM agents in smart city management, leveraging both the inherent language processing abilities of LLMs and the distributed problem solving capabilities of multi-agent systems for the improvement of urban...
The growing deployment of distributed renewable generation, storage, electric vehicles, heat pumps, smart buildings, and controllable demand is expanding the flexibility available to local energy systems. Energy communities provide the governance con...
Development of distributed Multi-Agent Reinforcement Learning (MARL) algorithms has attracted an increasing surge of interest lately. Generally speaking, conventional Model-Based (MB) or Model-Free (MF) RL algorithms are not directly applicable to th...
The Internet of Things (IoT) comprises a vast number of digitally networked devices. Machine learning (ML), deep learning (DL), and federated learning (FL), all subfields of artificial intelligence (AI), have recently been investigated as cybersecuri...
This review paper examines the integration of artificial intelligence (AI) in wireless communication, focusing on cognitive radio (CR), spectrum sensing, and dynamic spectrum access (DSA). As the demand for spectrum continues to rise with the expansi...
Timely and precise identification of breast cancer is crucial for enhancing clinical outcomes; however, current AI systems frequently exhibit deficiencies in transparency, trustworthiness, and the capacity to assimilate varied data modalities. We int...
Agentic artificial intelligence (AI) is emerging as a paradigm for next-generation smart grids, enabling autonomous decision-making, adaptive coordination, and resilient control in complex cyber–physical environments. Unlike traditional AI mode...
The rapid evolution of Generative Artificial Intelligence (GenAI) is reshaping the energy sector, enabling new levels of adaptability, efficiency, and user-centric interaction. This review systematically maps and critically evaluates the chosen liter...
Zero-shot generalization to out-of-distribution (OOD) teammates and opponents in multi-agent systems (MASs) remains a fundamental challenge for general-purpose AI, especially in open-ended interaction scenarios. Existing multi-agent reinforcement lea...
The integration of unmanned aerial vehicles (UAVs) as aerial base stations has emerged as a key enabler for next-generation wireless networks, particularly in disaster recovery, temporary events, and infrastructure-deficient regions. However, multi-U...
AI-based internet of things (IoT) systems increasingly require upstream decision-making mechanisms to identify emerging technologies that may shape future sensing–memory–communication–computation capabilities (SMCC). However, early...
The radial distribution networks are designed for unidirectional power flows and are passive in nature. However, with the penetration of Distributed Generation (DG), the power flow becomes bidirectional and the network becomes active. The integration...
In complex task environments in both nature and human society, structuralviolations of expectation (VoE) occur with non-trivial frequency. Agents that are designed to operate in such environments must be capable of open-world learning (OWL), defined...
The rapid proliferation of distributed energy resources (DERs), including photovoltaics, wind power, battery energy storage, and electric vehicles, has transformed traditional power systems into highly decentralized and data-rich environments. Virtua...
Collaborative intelligent sensing in the Social Internet of Things (Social IoT) relies on distributed AI-enabled sensors to support complementary information sharing, multimodal perception, and real-time autonomous decision-making. Under high-load co...
Recently, the need for unified orchestration frameworks that can manage extremely heterogeneous, distributed, and resource-constrained environments has emerged due to the rapid development of cloud, edge, and IoT computing. Kubernetes and other tradi...
This research introduces a new intelligent routing and resource allocation algorithm called Graph Sample and Aggregate-Multi-Agent Proximal Policy Optimization (GraphSAGE-MAPPO), which targets dynamic wireless mesh networks like those present in emer...
Current power systems are facing noticeable power quality (PQ) performance deterioration, which has been attributed to nonlinear loads, distributed generation, and extensive renewable energy infiltration (REI). These conditions cause voltage sags, ha...
The cold-chain supply of perishable fruits continues to face challenges such as fuel wastage, fragmented stakeholder coordination, and limited real-time adaptability. Traditional solutions, based on static routing and centralized control, fall short...
This article presents ELA Tutor, a generative AI-based Intelligent Tutoring System (ITS) built on a Multi-Agent System (MAS) architecture and implemented using the n8n platform to support personalized learning processes in higher education. The propo...
Maritime unmanned aerial vehicles (UAVs) are increasingly transforming ocean, coastal, port, and offshore operations through rapid sensing, intelligent communication, autonomous perception, and cooperative decision support. This trend-oriented review...
Internet-of-Things (IoT) technologies have been steadily adopted and embedded into energy infrastructure following the rapid transformation of energy grids through distributed consumption, renewables generation, and battery storage. The data streams...
Background: Blockchain and Multi-Agent System (MAS) are increasingly combined to support decentralized, secure, and autonomous peer-to-peer energy trading in microgrid environments. Objectives: This systematic review investigates how blockchain and M...
Mobile edge computing networks (MECNs) based on hierarchical cloud computing have the ability to provide abundant resources to support the next-generation internet of things (IoT) network, which relies on artificial intelligence (AI). To address the...
Once an active distribution network of a cyber-physical system is in alert state, it is vulnerable to cross-domain cascading failures. It is necessary to transit the state of an active distribution network of cyber-physical system from an alert state...
The Internet of Things (IoT) encompasses multiple fast-emerging technologies controlling and connecting millions of new devices every day in several application domains. The increased number of interconnected IoT devices, their limited computational...
The integration of artificial intelligence (AI) into medical practice is a paradigmatic transformation that compels a reconsideration of the very conceptual structure of bioethics. We argue that this transformation is the local symptom of a wider mut...
The evolution toward sixth generation (6G) wireless networks promises higher performance, greater flexibility, and enhanced intelligence. However, it also introduces a substantially enlarged attack surface driven by open, disaggregated, and multi-ven...
Context. Asynchronous messaging is increasingly used to support human–machine interactions, generally implemented through chatbots. Such virtual entities assist the users in activities of different kinds (e.g., work, leisure, and health-related) and...
The rapid growth of renewable integration and active consumer participation has made modern power grids increasingly complex and dynamic, where maintaining balanced and efficient energy distribution remains a central challenge. This paper introduces...