As technological advancements increase exponentially, mobile phones become smarter with machine learning and artificial intelligence algorithms. These advancements have allowed mobile phone users to perform most of their daily routine tasks on mobile...
Bug reports in open-source projects are often incomplete or low in quality, which reduces maintenance efficiency. To address this issue, we propose AgentReport, a multi-agent pipeline based on large language models (LLMs). AgentReport integrates QLoR...
During automated negotiations, intelligent software agents act based on the preferences of their proprietors, interdicting direct preference exposure. The agent can be armed with a component of an opponent’s modeling features to reduce the unce...
In the last few years, we witnessed a growing body of literature about automated negotiation. Mainly, negotiating agents are either purely self-driven by maximizing their utility function or by assuming a cooperative stance by all parties involved in...
Market volatility and resource constraints pose significant resilience challenges to small and medium-sized enterprises (SMEs). Although AI-agent automation, agile marketing, and customer relationship management (CRM) offer powerful individual soluti...
The evolving landscape of cybersecurity threats demands the modernization of Security Operations Centers (SOCs) to enhance threat detection, response, and mitigation. Security Orchestration, Automation, and Response (SOAR) platforms play a crucial ro...
Automating a factory where robots are involved is neither trivial nor cheap. Engineering the factory automation process in such a way that return of interest is maximized and risk for workers and equipment is minimized is hence, of paramount importan...
Data governance for responsible AI systems remains challenged by the lack of automated tools that can apply robust privacy-preserving techniques without destroying analytical value. We propose AnonymAI, a novel methodological framework that integrate...
Sustainable supply chain management (SCM) demands efficiency while minimizing environmental impact, yet conventional automation lacks adaptability. This paper presents SustAI-SCM, an AI-powered framework integrating agentic intelligence to automate s...
The increasing volume, velocity, and sophistication of cyber threats have placed immense pressure on modern Security Operations Centers (SOCs). Traditional rule-based and manual processes are proving insufficient, leading to alert fatigue, delayed re...
Existing autosamplers are frequently applied only for subjecting the samples to the instruments for injection. In our study, we have set up a TriPlusRSH autosampler mounted on a GC-FID-MS/MS system using the new Method Composer and Script Editor soft...
This study presents the optimization of an automated mushroom substrate irrigation system by integrating a Soft Actor-Critic (SAC) reinforcement learning agent with a recursive LSTM prediction model. The system, based on a Siemens S7-1200 PLC, CS650...
Connected and automated vehicles (CAVs) require multiple tasks in their seamless maneuverings. Some essential tasks that require simultaneous management and actions are motion planning, traffic prediction, traffic intersection management, etc. A few...
As the scale of the system and network grows, IT infrastructure becomes more complex and hard to be managed. Many organizations have a serious problem to manage their system and network security. In addition, vulnerabilities of hardware and software...
This exploratory proof-of-concept study investigated the simultaneous deployment of autonomous, persona-driven Artificial Intelligence (AI) agents across multiple social media platforms using the ElizaOS framework. We developed three platform-specifi...
Enhancing fuel efficiency in public transportation requires the integration of complex multimodal data into interpretable, decision-relevant insights. However, traditional analytics and visualization methods often yield fragmented outputs that demand...
Advances in Artificial Intelligence (AI) and Large Language Models (LLMs) have transformed accounting by automating repetitive tasks and enhancing the efficiency of financial reporting. However, their implementation raises challenges related to bias,...
This paper investigates the feasibility of using an agent-based framework to configure, control and coordinate dynamic, real-time robotic operations with the use of ontology manufacturing principles. Production automation agents use ontology models t...
Recently, a multi-agent based network automation architecture has been proposed. The architecture is named multi-agent based network automation of the network management system (MANA-NMS). The architectural framework introduced atomized network funct...
Agent-based automated negotiation aims to enhance decision-making processes by predefining negotiation rules, strategies, and objectives to achieve mutually acceptable agreements. However, most existing research primarily focuses on modeling the form...
Background: Intralogistics systems face growing challenges from globalization, individualization, and shorter product life cycles, demanding flexible and responsive solutions beyond traditional centralized control. Decentralized, agent-based approach...
Automated negotiation in multi-agent electronic commerce environments relies heavily on efficient and reliable matching mechanisms to connect negotiation participants. However, existing matching protocols often fail to ensure transaction security and...
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Electronic fetal monitoring (EFM) systems integrate many previously separate clinical activities related to fetal monitoring. Promoting the use of ubiquitous fetal monitoring services with real time status assessments requires a robust information pl...
Without any more delay, individuals are urged to adopt more sustainable behaviors to fight climate change. New digital systems mixed with engaging and gamification mechanisms could play an important role in achieving such an objective. In particular,...
The continuous changes of the market and customer demands have forced modern automation systems to provide stricter Quality of service (QoS) requirements. This work is centered in automation production system flexibility, understood as the ability to...
E-commerce is increasingly competitive and there is a constant need for new approaches and technology to facilitate exchange. Emerging techniques include the use of artificial intelligence (AI). One AI tool that has sparked interest in e-commerce is...
Consensus building among agents is crucial in multi-agent systems because each agent acts independently according to its utility function, and conflict among agents can occur. Therefore, automated negotiation is an essential technology for efficientl...
The implementation of a multi-microgrid (MMG) system with multiple renewable energy sources enables the facilitation of electricity trading. To tackle the energy management problem of an MMG system, which consists of multiple renewable energy microgr...
Reliable access to electricity is still a challenge in many developing countries. Indeed, rural areas in sub-Saharan Africa and developing countries such as India still encounter frequent power outages. Local energy markets (LEMs) have emerged as a l...
In the context of global suburbanization and population aging, a low-speed, automated vehicle (LSAV) system provides essential mobility services in suburban residential areas. Although extensive studies on shared autonomous vehicle (SAV) services hav...
The growth of Agentic AI systems in Industrial Automation has brought forth new cybersecurity issues which in turn put at risk the reliability and integrity of these systems. In this study we look at the cybersecurity issues in industrial automation...
Automated Manufacturing Systems (AMS) consisting of many cooperating devices incorporated into multiple cooperating production lines, sharing common resources, represent industrial Multi-Agent Systems (MAS). Deadlocks may occur during operation of su...
This paper presents a multi-agent reinforcement learning (MARL) algorithm to address the scheduling and routing problems of multiple automated guided vehicles (AGVs), with the goal of minimizing overall energy consumption. The proposed algorithm is d...
Despite rapid advances in vehicle intelligence and connectivity, there is still a significant period in mixed traffic where connected, automated vehicles and human-driven vehicles coexist. The behavioral uncertainty of human-driven vehicles makes dec...
The accelerating integration of Artificial Intelligence (AI) in Industrial Automation has established Reinforcement Learning (RL) as a transformative paradigm for adaptive control, intelligent optimization, and autonomous decision-making in smart fac...
Urban systems are transforming as artificial intelligence (AI) evolves from automation to Agentic Urban AI (AI systems with autonomous goal-setting and decision-making capabilities), which independently define and pursue urban objectives. This shift...
Network security tools are indispensable in testing and evaluating the security of computer networks. Existing tools, such as Hping3, however, offer a limited set of options and attack-specific configurations, which restrict their use solely to well-...
With the advancement of digitization in the era of Industry 4.0 (I4.0), highly automated, semi-autonomous, and fully autonomous systems are emerging. Within this context, multi-agent systems (MAS) offer a promising approach for automating tasks and p...
The subway power supply system, as a critical component of urban rail transit infrastructure, plays a pivotal role in ensuring operational efficiency and safety. However, current systems remain heavily dependent on manual interventions for fault diag...
The technologies related to green energy, smart cities and similar areas being dynamically developed in recent years, face frequently problems of a computational nature rather than a technological one. The example is the ability of accurately predict...
In liberalized markets, consumers can choose their electricity suppliers or be part of an energy community. The problem with communities is that they may not have enough weight to trade in markets, which can be overcome by forming coalitions. Electri...
Reinforcement learning-based approaches are widely studied in the literature for solving different control tasks for Connected and Autonomous Vehicles, from which this paper deals with the problem of lateral control of a dynamic nonlinear vehicle mod...
The smart-house technology aims to increase home automation and security with reduced energy consumption. A smart house consists of various intelligent sensors and actuators operating on different platforms with conflicting objectives. This paper pro...
An efficient participation of prosumers in power system management depends on the quality of information they can obtain. Prosumers actions can be performed by automated agents that are operating in time-changing environments. Therefore, it is essent...
In the context of automated vehicles, transparency of in-vehicle intelligent agents (IVIAs) is an important contributor to driver perception, situation awareness (SA), and driving performance. However, the effects of agent transparency on driver perf...
Smart cities are Hyper-Connected Digital Environments (HCDEs) that transcend the boundaries of natural, human-made, social, virtual, and artificial environments. Human activities are no longer confined to a single environment as our presence and inte...
Background: With advancements in Generative Artificial Intelligence, various industries have made substantial efforts to integrate this technology to enhance the efficiency and effectiveness of existing processes or identify potential weaknesses. Con...
Background: The habitat structure, the environmental impact, the market acceptance, the changes in consumers’ preferences, and the pandemic urged for innovative solutions in urban last-mile delivery. Parcel lockers are among the most preferred...
In today’s high-stakes arenas—from healthcare to defense—algorithms are advancing at an unprecedented pace, yet they still lack a crucial element of human decision-making: an instinctive caution that helps prevent harm. Inspired by...
Formal verification of distributed systems is essential, especially in mission-critical systems that cannot be restarted. Such are space systems in which satellites read sensor values and autonomously make actuator decisions based on them, and ground...
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