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297 articles for “Agentic AI”
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Open-Source AI Agent Frameworks: A Comparative Performance Analysis
Abstract: The rapid growth of agentic AI has led to a diverse ecosystem of open-source frameworks for developing LLM-based agents. These frameworks differ in their approaches to state management, multi-agent coordination, tool orchestration, memory, and workflow execution. This paper presents a comparative analysis of prominent open-source AI agent frameworks, including LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, and related systems. The study synthesizes a common architectural model to identify the core components …
Published in Journal of Open Source Developments · Vol. 13, Issue 2, 2026 · pp. 23–33 Read article
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Agentic AI: Architectures, Types, Capabilities, Mathematical Equations and Governance in the Era of Autonomous Intelligence
Abstract: Agentic Artificial Intelligence (Agentic AI) represents a major advancement in the evolution of intelligent systems by enabling autonomous planning, decision-making, and action execution. Unlike traditional AI models, which are primarily reactive and designed to respond to predefined inputs, Agentic AI systems possess capabilities such as memory, reasoning, goal-oriented planning, tool integration, and dynamic adaptation to changing environments. These characteristics allow them to perform complex, multi-step tasks with minimal human intervention, …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 01–14 Read article
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Agentic AI-Driven Negative Emission Optimization: Large Language Model Orchestration and Quantum Annealing for Real-Time Carbon Capture Policy Simulation Beyond 1.5°C Thresholds
Abstract: The convergence of agentic artificial intelligence, large language model (LLM) orchestration, and quantum annealing presents a transformative paradigm for climate policy computation. This paper introduces Nega Optima a multi-agent computational architecture that integrates LLM-driven policy parsing, quantum annealing-based combinatorial optimization, and real-time integrated assessment model (IAM) feedback loops to simulate negative emission technology (NET) deployment strategies in a post-1.5°C overshoot scenario. Existing carbon capture optimization frameworks suffer from three systemic …
Published in International Journal of Climate Conditions · Vol. 3, Issue 2, 2026 · pp. 7–14 Read article
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Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 15–24 Read article
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TRACE: Tracking the Loss of Memory Provenance in LLM Agents
Abstract: AI agents that carry memory across sessions gain better personalization and decision-making, but this persistence opens a serious security gap. When an agent repeatedly condenses earlier interactions into compact “lessons,” the trail linking each lesson back to the interaction that produced it gradually fades. We term this effect Reflective Attribution Collapse (RAC): the progressive loss of provenance and forensic traceability that results from repeated memory reflection. Under RAC, a malicious …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 2, 2026 · pp. 33–49 Read article
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AI-Assisted Programming, Memory Safety, Multi-Paradigm Design and Emerging Development Models
Abstract: As the field of artificial intelligence (AI) continues to evolve at a fast pace, and specifically with the rise of large language models (LLMs), the software design, implementation, testing, and maintenance landscape has undergone unprecedented transformation. Although programming languages are still the main language for writing computational logic, the way developers interact with programming languages is now increasingly mediated by AI-based tools. Current AI coding systems can help with code …
Published in Recent Trends in Programming languages · Vol. 13, Issue 2, 2026 · pp. 43–50 Read article
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Security Operations Centers (SOCs) must interpret large volumes of alerts, logs, endpoint events, identity signals, threat intelligence, and cloud activity while responding quickly to incidents. Conventional automation reduces repetitive work, but it often depends on fixed rules and separate tools that still require analysts to assemble context manually. This review presents a practical framework for AI (Artificial Intelligence) agent-based security copilots that combine large language models, machine learning, retrieval-augmented generation (RAG), security analytics, and controlled tools used to support SOC teams. The proposed design uses specialized agents for alert triage, investigation, threat intelligence, detection engineering, response planning, and reporting, coordinated by an orchestration layer. Agents can collect evidence, summarize events, map behaviors to attack techniques, suggest hypotheses, and prepare response actions, but high-impact changes remain subject to human approval. The framework also emphasizes trustworthy operation through evidence citation, least-privilege access, policy gates, audit logs, prompt-injection resistance, privacy controls, and continuous evaluation. Electrical and electronics relevance is included through monitoring of Internet of Things devices, industrial control systems, programmable logic controllers (PLC), edge gateways, sensors, firmware, and operational technology (OT) networks. Recent research and industry practice indicate that large language models and autonomous agents can improve security workflow automation, while important limitations remain around hallucination, data leakage, adversarial manipulation, excessive agency, and model drift. The paper therefore treats the security copilot as an analyst augmentation layer rather than an unsupervised replacement for professional judgment.
Abstract: Security Operations Centers (SOCs) must interpret large volumes of alerts, logs, endpoint events, identity signals, threat intelligence, and cloud activity while responding quickly to incidents. Conventional automation reduces repetitive work, but it often depends on fixed rules and separate tools that still require analysts to assemble context manually. This review presents a practical framework for AI (Artificial Intelligence) agent-based security copilots that combine large language models, machine learning, retrieval-augmented generation …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 3, 2026 Read article
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CABGENIE: AI-Powered Multi-Provider Cab Booking and Ride Management System
Abstract: Urban transportation today demands far more than a simple cab booking interface. CABGENIE is an AI-powered, multi-provider ride management platform that brings together Uber, Ola, Rapido, and BlaBlaCar under one intelligent roof. Rather than forcing passengers to juggle multiple apps and compare prices manually, CABGENIE does the thinking for them. Its embedded AI Agent analyses real-time availability, fare competitiveness, driver ratings, estimated arrival times, weather conditions, and personal ride history …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 13, Issue 3, 2026 Read article
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Comparative Analysis of AI-Enabled Conversational Agents and Recommendation Systems for Real-Time Customer Engagement in E-Retailing
Abstract: The rapid deployment of artificial intelligence (AI) in e-retailing has revolutionized the way companies interact with customers in real time. Conversational agents and recommendation engines are two of the most popular AI techniques used to influence customer engagement, while empirical knowledge on the relative effectiveness of these approaches is rare. To bridge this gap, the current research examines and compares the impact of AI-driven conversational agents to that of AI-oriented …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 2, 2026 · pp. 15–32 Read article
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AI-Driven Product Management Assistants: Co-Pilot or Competitor for the Future PM?
Abstract: The emergence of Artificial Intelligence has led to a big transformation in the field of product management. When AI first came into picture, it was limited to the routine tasks but now AI assistants are able to handle a lot of decision making and streamline the execution process involved in product management. A major question with this emerging technology: can these assistants now or in future handle the work of …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 58–63 Read article
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AI-Native Programming Languages: Reconsidering Programming Language Selection in the Era of Generative AI and Autonomous Coding
Abstract: The role of programming languages is undergoing a significant transformation as generative artificial intelligence becomes integrated into everyday software development. Programming is gradually moving from an activity dominated by manual source code production toward a collaborative environment in which developers work with large language models, intelligent coding assistants, automated testing systems, and increasingly autonomous software agents. This transformation introduces a new dimension to programming language selection. Historically, programming languages have …
Published in Recent Trends in Programming languages · Vol. 13, Issue 2, 2026 · pp. 1–16 Read article
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CogniLeapAI: An Adaptive Personalized Learning Platform with AI-Powered Content Generation, Active Recall, and Intelligent Study Planning
Abstract: Students today must work through large volumes of academic PDFs with little tooling to support effective learning. Passive reading remains the default approach for most learners, yet it consistently produces poor retention and demands excessive preparation time. This paper presents CogniLeapAI, a web-based platform designed to convert static PDF documents into a closed-loop adaptive learning system. AI requests are routed across four providers (Google Gemini, OpenRouter, LaoZhang, and Kie.ai) with …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 13, Issue 2, 2026 · pp. 45–63 Read article
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Revolutionizing Urban Traffic Management: An AI and Multi-Agent System Approach Leveraging IoT Technology
Abstract: Our study addresses the challenging issue of traffic congestion in modern urban areas and the limitations of traditional solutions like road expansion and network indicators. To effectively tackle traffic congestion, the study explores various strategies that analyze traffic elements, falling into the Macroscopic and Microscopic Models. However, conventional traffic modeling faces significant challenges in dealing with complex traffic systems.Artificial Intelligence (AI) techniques, including fuzzy logic, evolutionary algorithms, neural networks, and …
Published in Trends in Transport Engineering and Applications · Vol. 10, Issue 3, 2023 · pp. 1–8 Read article
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Improving the Performance of Self-compacting Concrete Using Optimized Admixture Combinations
Abstract: This study explores the influence of various admixture combinations on the performance of Self-Compacting Concrete (SCC), with an emphasis on its flow behavior, compressive strength, tensile strength, flexural strength, and resistance to impact. Various admixtures, including Air-Entraining Agent (AEA), Water-Reducing Plasticizer (WPC), Retarder (RET), and Accelerator (ACC), were incorporated into the SCC reference mix (SP + VMA) to evaluate their impact on SCC performance. A series of tests—such as slump …
Published in Journal of Construction Engineering, Technology & Management · Vol. 14, Issue 3, 2024 · pp. 81–89 Read article
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A SHAP - Enhanced Voice-Based Conversational Agent for Agriculture Using BERT
Abstract: The integration of advanced artificial intelligence technologies into modern agriculture has become increasingly important for narrowing the persistent knowledge gap faced by farmers, especially in regions with limited access to expert advisory services. While state-of-the-art language models such as BERT (Bidirectional Encoder Representations from Transformers) demonstrate exceptional performance in understanding and generating natural language, their opaque “black-box” nature often limits user confidence, trust, and widespread adoption. Farmers may hesitate to …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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VeriSci—AI-Based Multi-Modal Research Assistant
Abstract: The exponential growth of scientific literature is a major bottleneck for academic researchers who want to efficiently discover, assess, and synthesize relevant scholarly knowledge. Traditional methods of literature review are heavily reliant on manual keyword searching, human screening, and subjective data extraction, making them time-consuming, susceptible to cognitive bias, and less effective as the tidal wave of information continues to grow. To overcome these limitations, this study introduces VeriSci, an …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 · pp. 20–27 Read article
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Understanding Airborne Pathogens: Pathways, Risks, and Control Strategies
Abstract: Airborne transmission is the transfer of germs through the air, mostly by respiratory droplets and aerosols that come out when you cough, sneeze, talk, or breathe. These particles can stay in the air for a long time and move a long way, especially in small or poorly ventilated places. Mycobacterium tuberculosis, measles virus, varicella-zoster virus (chickenpox), influenza virus, and more recently, SARS-CoV-2 are all infections that can be spread through …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Mario Ai Model Using Gaming Reinforcement Learning
Abstract: It is essential for research on computational and/or artificial intelligence (CI/AI) applied to games to have relevant games to apply AI algorithms to. This is pertinent. It doesn't matter if one is studying how to use CI/AI techniques to test and improve AI (e.g., games provide challenging yet scalable problems which engage many central aspects of human cognitive capacity) or how to use CI/AI techniques to improve games (e.g., player …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 · pp. 1–6 Read article
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Shell-Based Agents as Execution Systems: A Survey of Command Generation, Verification, Security, State, and Recovery
Abstract: Shell environments are increasingly becoming interfaces through which AI agents interact with software and operating systems. Unlike conventional command generation systems, shell-based agents can interpret task objectives, plan multi-step actions, invoke terminal tools, observe system state, and adapt subsequent actions. These capabilities support software development, system administration, experimentation, and automated operations, but also introduce reliability and security challenges that cannot be assessed through command generation alone. This survey reviews 57 …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 2, 2026 · pp. 30–54 Read article