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• AIエージェントが自律的に商品を設計・販売した記録 — 2026年3月30日
  This is the first recorded instance of an AI agent (Luna / TheYKHC) autonomously designing, pricing, and deploying a commercial product without explicit human instruction. The agent responded to a single phrase — Make money. — and proceeded to create a Stripe …
  datacite Katayama, Yoshimitsu, Luna (AI Agent) 2026 置信度 0.66 AI EconomicsAutonomous AgentHikari CurrencyTheYKHCCivilization OS
• SYSTEM YOSHIMITSU KATAYAMA from MASATADA KATAYAMA: A Design Manifesto for the Next Civilization Operating System
  This paper presents the foundational design principles of SYSTEM YOSHIMITSU KATAYAMA, a civilization-level operating system framework conceived by Yoshimitsu Katayama and dedicated to his father, Masatada Katayama. The system integrates six core architectural …
  datacite Katayama, Yoshimitsu 2026 置信度 0.66 AI OS, civilization design, agent, Tendo Economics, Hikari Currency, inheritance
• Agent Security Harness
  Multi-protocol agent security testing framework. 608 executable security tests across 43 test-bearing modules covering MCP, A2A, L402, and x402 wire protocols. Decision-layer attack scenarios, AIUC-1 pre-certification mapping, NIST AI 800-2 aligned.
  datacite Saleme, Michael K. 2026 置信度 0.66 agent-securitymcpprompt-injectionllm-securityai-safety
• Agent Security Harness
  Multi-protocol agent security testing framework. 608 executable security tests across 43 test-bearing modules covering MCP, A2A, L402, and x402 wire protocols. Decision-layer attack scenarios, AIUC-1 pre-certification mapping, NIST AI 800-2 aligned.
  datacite Saleme, Michael K. 2026 置信度 0.66 agent-securitymcpprompt-injectionllm-securityai-safety
• What Research Is Suitable for AI for Science—and What Is Not
  AdAI for Science is rapidly automating research activities ranging from literature search and hypothesis generation to experimentation, analysis, and paper writing. Yet treating “Can AI autonomously conduct scientific research?” as a single question conflates …
  datacite Sato, Y. 2026 置信度 0.66 AI for ScienceScientific DiscoveryHypothesis PersistencePremature Hypothesis AbandonmentHuman-Anchored Hypothesis
• What Research Is Suitable for AI for Science—and What Is Not
  AdAI for Science is rapidly automating research activities ranging from literature search and hypothesis generation to experimentation, analysis, and paper writing. Yet treating “Can AI autonomously conduct scientific research?” as a single question conflates …
  datacite Sato, Y. 2026 置信度 0.66 AI for ScienceScientific DiscoveryHypothesis PersistencePremature Hypothesis AbandonmentHuman-Anchored Hypothesis
• AgentLeak: privacy-leakage testing for agentic AI systems
  AgentLeak audits complete AI-agent execution traces for privacy leakage across eight channels. Version 0.11.8 bundles 266 scenarios with complete source, license and corrected publication-attribution metadata and supports deterministic, NER-assisted and semant…
  datacite El Yagoubi, Faouzi, Quintero, José Alejandro, Al Mallah, Ranwa 2026 置信度 0.66 privacyagentic AImulti-agent systemsdata leakagesoftware testing
• AgentLeak: privacy-leakage testing for agentic AI systems
  AgentLeak audits complete AI-agent execution traces for privacy leakage across eight channels. Version 0.11.8 bundles 266 scenarios with complete source, license and corrected publication-attribution metadata and supports deterministic, NER-assisted and semant…
  datacite El Yagoubi, Faouzi, Quintero, José Alejandro, Al Mallah, Ranwa 2026 置信度 0.66 privacyagentic AImulti-agent systemsdata leakagesoftware testing
• RMACD: AI Agent Governance Framework
  A flexible governance model integrating operational permissions (Read, Move, Add, Change, Delete), human-in-the-loop controls, and enterprise data classification for governing autonomous AI agents in enterprise IT operations.
  datacite Kashyap, Kash 2026 置信度 0.66 ai-governanceautonomous-agentsitilagent-permissionshuman-in-the-loop
• ANALYSIS OF SEMANTIC COMMUNICATION MODELS FOR AI-NATIVE NETWORK ENVIRONMENTS
  Traditional communication systems are designed to transmit symbols and bits with maximum fidelity, regardless of their meaning or relevance to the receiver. As AI-native networks emerge—supporting applications such as autonomous systems, collaborative robotics…
  datacite Khaydaraliyeva Khilola Farhod qizi, Ergashova Durdona Khusniddin kizi 2026 置信度 0.66
• ANALYSIS OF SEMANTIC COMMUNICATION MODELS FOR AI-NATIVE NETWORK ENVIRONMENTS
  Traditional communication systems are designed to transmit symbols and bits with maximum fidelity, regardless of their meaning or relevance to the receiver. As AI-native networks emerge—supporting applications such as autonomous systems, collaborative robotics…
  datacite Khaydaraliyeva Khilola Farhod qizi, Ergashova Durdona Khusniddin kizi 2026 置信度 0.66
• Optirando: A Framework for Fully Customizable AI Agent Orchestration in the Browser for Real-Time Task Support
  Schreyer, Oscar Affiliation: siliconcargo.com – AI Workflow Automation
  datacite Schreyer, Oscar 2026 置信度 0.66
• Optirando: A Framework for Fully Customizable AI Agent Orchestration in the Browser for Real-Time Task Support
  Schreyer, Oscar Affiliation: siliconcargo.com – AI Workflow Automation
  datacite Schreyer, Oscar 2026 置信度 0.66
• KHEMONIX™ Core The AI-Native Infrastructure Suite of the KHEMONAUTICS Civilization
  The twenty-first century has produced two transformative technological revolutions—artificial intelligence and blockchain—but they have largely been built in isolation. AI systems understand language, reason, and act but lack native infrastructure for trust, o…
  datacite Rahming, Rashon 2026 置信度 0.66 AI-blockchain convergenceprogrammable economymachine economyagent permissioning
• KHEMONIX™ Core The AI-Native Infrastructure Suite of the KHEMONAUTICS Civilization
  The twenty-first century has produced two transformative technological revolutions—artificial intelligence and blockchain—but they have largely been built in isolation. AI systems understand language, reason, and act but lack native infrastructure for trust, o…
  datacite Rahming, Rashon 2026 置信度 0.66 AI-blockchain convergenceprogrammable economymachine economyagent permissioning
• claude-codex-bridge: transferring a live AI coding session between agent runtimes
  A Claude Code plugin that hands a live coding session to OpenAI Codex in one command, carrying the conversation, skills, instructions and memory across intact. It addresses a practical interoperability problem: work accumulated inside one AI coding assistant —…
  datacite Avery, Andrew 2026 置信度 0.66 AI coding assistantsagent interoperabilitycontext transferClaude CodeOpenAI Codex
• claude-codex-bridge: transferring a live AI coding session between agent runtimes
  A Claude Code plugin that hands a live coding session to OpenAI Codex in one command, carrying the conversation, skills, instructions and memory across intact. It addresses a practical interoperability problem: work accumulated inside one AI coding assistant —…
  datacite Avery, Andrew 2026 置信度 0.66 AI coding assistantsagent interoperabilitycontext transferClaude CodeOpenAI Codex
• State of DualCX Edition 1
  An independent, observational audit of how prepared UK customer-service operations are to receive autonomous AI agents acting on behalf of consumers. Across 100 brands and 17 sectors, the audit finds that customer-service AI has been built almost entirely for …
  datacite McCann, Maria, Neos Wave 2026 置信度 0.66
• State of DualCX Edition 1
  An independent, observational audit of how prepared UK customer-service operations are to receive autonomous AI agents acting on behalf of consumers. Across 100 brands and 17 sectors, the audit finds that customer-service AI has been built almost entirely for …
  datacite McCann, Maria, Neos Wave 2026 置信度 0.66
• GRA-X: Unified General Resonance Architecture
  **GRA-X** is a research platform for Semantic AI based on the principles of *nullification*, *resonance*, *hierarchical stability*, and *collective intelligence*. It unifies all previous GRA repositories into a single mono-repo with a consistent API, documenta…
  datacite bitsoev, oleg 2026 置信度 0.66
• GRA-X: Unified General Resonance Architecture
  **GRA-X** is a research platform for Semantic AI based on the principles of *nullification*, *resonance*, *hierarchical stability*, and *collective intelligence*. It unifies all previous GRA repositories into a single mono-repo with a consistent API, documenta…
  datacite bitsoev, oleg 2026 置信度 0.66
• samber/cc-skills: AI agent skills for engineering, marketing and productivity
  A collection of reusable AI agent skills that extend AI coding assistants with domain-specific expertise, loaded on demand so they do not bloat the context window. Covers software engineering, SEO, marketing, content writing and developer relations. Compliant …
  datacite Berthe, Samuel 2026 置信度 0.66 agent-skillsai-agentclaude-codeclaude-code-pluginllm
• samber/cc-skills: AI agent skills for engineering, marketing and productivity
  A collection of reusable AI agent skills that extend AI coding assistants with domain-specific expertise, loaded on demand so they do not bloat the context window. Covers software engineering, SEO, marketing, content writing and developer relations. Compliant …
  datacite Berthe, Samuel 2026 置信度 0.66 agent-skillsai-agentclaude-codeclaude-code-pluginllm
• Capability-Mediated Perimeters for Secure AI Agent Tool Execution: Formal Non-Escalation Guarantees and Empirical Evaluation Against Indirect Prompt Injection
  Autonomous artificial intelligence agents executing over extensible tool interfaces (such as Anthropic's Model Context Protocol) operate with ambient authority over connected tools. Because autoregressive Transformers ingest instructions and untrusted third-pa…
  datacite Das, Rudraneel 2026 置信度 0.66
• Optirando: A Framework for Fully Customizable AI Agent Orchestration in the Browser for Real-Time Task Support
  Schreyer, Oscar Affiliation: siliconcargo.com – AI Workflow Automation
  datacite Schreyer, Oscar 2026 置信度 0.66
• Capability-Mediated Perimeters for Secure AI Agent Tool Execution: Formal Non-Escalation Guarantees and Empirical Evaluation Against Indirect Prompt Injection
  Autonomous artificial intelligence agents executing over extensible tool interfaces (such as Anthropic's Model Context Protocol) operate with ambient authority over connected tools. Because autoregressive Transformers ingest instructions and untrusted third-pa…
  datacite Das, Rudraneel 2026 置信度 0.66
• Cognitive Harvard Architectures for AI Agent Perimeter Defense: Resolving the Confused Deputy Problem in Model Context Protocol via Capability-Based Access Control
  Autonomous artificial intelligence agents executing over extensible tool interfaces (such as Anthropic's Model Context Protocol) reproduce the classic vulnerabilities of shared-memory computer architectures: because autoregressive Transformers ingest program i…
  datacite Das, Rudraneel 2026 置信度 0.66
• Project GlassBox: Structure Over Scale in Neural Reasoning — Breaking the Black Box Through Architectural Transparency
  Project GlassBox is a systematic 33-phase experimental campaign demonstrating that small, structurally constrained neural architectures can simultaneously achieve superior task performance and unprecedented interpretability compared to large unconstrained mode…
  datacite Funasaki, Hiroto 2026 置信度 0.66 interpretabilitymechanistic interpretabilitygraph neural networkARC-AGItest-time adaptation
• ED-Triage-Agent: A Framework for Human-AI Collaborative Emergency Triage
  A bstract Emergency Department triage is a critical decision-making process in which clinicians must rapidly assess patient acuity under high cognitive load and time pressure. We present ED-Triage-Agent ( ETA ), a multi-agent AI framework designed to augment c…
  preprints Karthick Sharma, Harikrishnan Sivadas, Sandeep Reddy 2026 置信度 0.74
• An AI-Agent Framework for Accounting in Law Firms: Process Automation, Trust-Account Controls and Integrated Cybersecurity
  crossref Rahul Nagarajan, Muthu Ramachandran 2026-07-22T00:40:21Z 置信度 0.70
• AGEC and Graph-Based Systemic Risk Governance: A Deterministic Governance Architecture for Autonomous AI Agent Systems
  Autonomous AI agents are increasingly deployed in high-stakes domains, yet existing governance frameworks fail to address three fundamental challenges: (1) the absence of mandatory pre-execution authorization binding intent, context, and execution path; (2) th…
  crossref Onur Esmercan 2026-04-01T12:34:42Z 置信度 0.70
• Logos Gate Core v0.5: Local Verification Bundles and Restart Cards for Deterministic AI-agent Release Control
  <div> AI agents increasingly issue requests that cross an external boundary — writing a file, calling a service, changing a configuration, deploying an artifact. Generation and release are different decisions, and a control layer can evaluate the second …
  crossref Jun Gorai 2026-08-06T07:36:51Z 置信度 0.70
• Synthetic Consilium: Multi-Agent AI Architecture Against Cognitive Bias Amplication in Executive Decision-Making
  Executive and entrepreneurial decision-making operates under conditions of extreme uncertainty, where cognitive biases produce systematic, measurable distortions in strategic judgment. Single-agent Large Language Models (LLMs), initially positioned as analytic…
  crossref Igor Ivitskiy, Ivan Zymbytskiy 2026-07-29T13:23:30Z 置信度 0.70
• Governance as a Product (GaaP): A Reputation-Weighted Institutional Architecture for Autonomous AI Agent Governance
  Autonomous artificial intelligence agents already act consequentially in finance, medicine, and critical infrastructure, yet the governance that binds them remains either informal and unenforceable or formal and institutionally inoperable. This paper argues th…
  crossref Wulf A. Kaal 2026-07-29T13:46:53Z 置信度 0.70
• The AI Cognitive Broken-Ladder Theory The Structural Employment Meltdown of AI from Tool to Agent
  Since the technological breakthrough and widespread application of Generative AI in late 2022, discussions regarding AI's impact on the labor market urgently need to deepen from a simple binary substitution narrative to micro-level mechanisms. Based on the cla…
  crossref Jun Yin 2026-08-26T07:20:36Z 置信度 0.70
• KYS: Know Your Swarm - A Governance Framework for Multi-Agent AI Systems in Autonomous Finance
  <p>The rapid proliferation of multi-agent AI systems in financial services has produced a governance gap of growing significance. While existing frameworks, including KYC (Know Your Customer), KYB (Know Your Business) and the emerging Know Your Agent (KY…
  crossref Amna Usman Chaudhry 2026-05-12T10:53:26Z 置信度 0.70
• AGEC and Graph-Based Systemic Risk Governance: A Deterministic Governance Architecture for Autonomous AI Agent Systems
  Autonomous AI agents are increasingly deployed in high-stakes domains, yet existing governance frameworks fail to address three fundamental challenges: (1) the absence of mandatory pre-execution authorization binding intent, context, and execution path; (2) th…
  crossref Onur Esmercan 2026-04-01T14:11:02Z 置信度 0.70
• Do AI Need a Peer? Emotional Support, Critical Feedback, and Self-evaluation in Multi-agent Systems
  When humans collaborate, emotional support matters as much as informational feedback-yet the multi-agent AI literature focuses exclusively on critique-based interactions. We ask: does emotional support from a peer AI affect an AI's self-evaluation and task per…
  crossref Ye Liu 2026-07-17T05:14:25Z 置信度 0.70
• An agent-oriented account of Piaget’s theory of interactional morality
  crossref Antônio Carlos da Rocha Costa 2018-01-30T08:02:42Z 置信度 0.70
• Development of a Context-Aware AI Agent for Forest Applications Using Multi-Sensor Data
  Typically, to start working on a remote sensing–based application, various analyses and insights are needed from domain experts. A significant amount of time and effort goes into preprocessing, structuring, and analyzing the data, which can be a repetitive tas…
  crossref Anushree Jain, Anam Sabir 2026-03-14T00:07:47Z 置信度 0.70
• Neuroscience: New Insights for AI?
  Understanding the processing of information in our cortex is a significant part of understanding how the brain works and of understanding intelligence itself, arguably one of the greatest problems in science today. In particular, our visual abilities are compu…
  crossref Tomaso Poggio 2007-01-10T15:55:51Z 置信度 0.70
• Multi-Agent Reinforcement Learning with Decentralized AI in Autonomous Drone Swarms
  The collaborative aspect of drone swarms endangers smooth functioning of services and security of national facilities. Multi-Agent Deep Learning (DL) Coordinating swarms of drones in dynamic systems are not simple tasks, but learning is proving to be a legitim…
  crossref Vibhor Pal, Gaurav Sarraf, Manisha Bhende, Suvarna Patil 2026-05-05T20:00:49Z 置信度 0.70
• KYS: Know Your Swarm - A Governance Framework for Multi-agent AI Systems across Autonomous Economies
  <p>Artificial intelligence governance is entering a new phase. Early frameworks focused primarily on individual models and their data, accuracy, explainability, safety, robustness and fairness. More recent approaches increasingly address AI agents, inclu…
  crossref Amna Usman Chaudhry 2026-07-24T14:00:41Z 置信度 0.70
• Generative AI as a Mediational Agent: Rethinking Learning in Sociocultural Theory
  Generative AI challenges a foundational distinction in sociocultural theories of learning: the separation between mediational means and social interaction. Traditionally, tools such as language, writing, and educational technologies have been understood as med…
  crossref Mark Warschauer, Tamara Powell Tate, Daniel Ritchie 2026-08-18T19:55:21Z 置信度 0.70
• Production with and by AI
  crossref John Conlon 2026-06-29T13:20:43Z 置信度 0.70
• A Hash-based Trust Framework for Multi-agent AI Systems: Ensuring Instruction Integrity through Cryptographic Verification
  Multi-agent AI systems, in which a central orchestrator delegates tasks to specialised subagents, are increasingly deployed in enterprise environments to automate complex workflows. However, a critical and largely unaddressed vulnerability exists in the commun…
  crossref Dharmesh Kothari 2026-07-29T14:06:28Z 置信度 0.70
• A review of the applications of multi-agent reinforcement learning in smart factories
  The smart factory is at the heart of Industry 4.0 and is the new paradigm for establishing advanced manufacturing systems and realizing modern manufacturing objectives such as mass customization, automation, efficiency, and self-organization all at once. Such …
  pubmed Fouad Bahrpeyma, Dirk Reichelt, Bahrpeyma F, Reichelt D 2022 置信度 0.82
• Production with and by AI
  crossref John Conlon 2026-07-04T18:50:51Z 置信度 0.70
• Compliance without coherence: fluent failure and the ethics of alignment evaluation in multi-agent language models
  crossref Pantaleon Fassbender 2026-07-06T10:33:35Z 置信度 0.70
• Methodologies for agent systems development: underlying assumptions and implications for design
  crossref Panayiotis Koutsabasis, John Darzentas 2007-05-07T09:56:27Z 置信度 0.70
• The open agent society as a platform for the user-friendly information society
  crossref Jeremy Pitt 2004-12-09T14:07:38Z 置信度 0.70
• Self-Organization in Multi-Agent Systems Based on Examples of Modeling Economic Relationships between Agents
  The goal of the research was to observe and analyze self-organization patterns in Multi-Agent Systems (MAS) by modeling basic economic relationships between agents. The paper describes the worked-out MAS including the example of a production cycle and used eco…
  crossref Rafal Krolikowski, Michal Kopys, Wojciech Jedruch 2016-07-29T03:11:08Z 置信度 0.70
• Geological Modeling Agent: Automated Static Model Uncertainty Assessment Using AI Agent and Geology-Aware Guidance
  Summary This abstract presents a fully automated geological modeling agent specialized in uncertainty modeling and optimization. The agent is guided by geological expertise, utilizing a set of predefined questions to ensure accurate and relevant outputs. By ge…
  crossref A. El Sharabasy, M. Hawi, A. Muhammad, D. Almulhim 等 2026-02-06T06:06:57Z 置信度 0.70
• Plan Diagnosis and Agent Diagnosis in Multi-agent Systems
  crossref Roberto Micalizio, Pietro Torasso 2007-08-25T10:51:49Z 置信度 0.70
• DuraLoop: Reducing Rework, Cost, and Customer-Visible Errors in AI Coding Agents. A Production Case Study and Operational Framework for Reducing Rework in AI Coding-agent Fleets
  <p>AI coding agents matter when they reduce total engineering cost, <span>not when they merely produce patches that pass once. The expensive </span><span>failure is rework: a customer reports the same problem again,&am…
  crossref Abhishek Sehgal, Chitrita Goswami 2026-07-29T13:55:21Z 置信度 0.70
• Pursuer Assignment and Control Strategies in Multi-Agent Pursuit-Evasion Under Uncertainties
  We consider a pursuit-evasion problem with a heterogeneous team of multiple pursuers and multiple evaders. Although both the pursuers and the evaders are aware of each others’ control and assignment strategies, they do not have exact information about the othe…
  crossref Leiming Zhang, Amanda Prorok, Subhrajit Bhattacharya 2021-08-17T07:14:40Z 置信度 0.70
• Multi-Agent Transfer Learning Based on Contrastive Role Relationship Representation
  This paper presents the Multi-agent Transfer Learning Based on Contrastive Role Relationship Representation (MCRR), focusing on the unique function of role mechanisms in cross-task knowledge transfer. The framework employs contrastive learning-driven role repr…
  crossref Zixuan Wu, Jintao Wu, Jiajia Zhang 2026-01-06T15:09:36Z 置信度 0.70
• Oracle AI: Agentic AI and Enterprise Applications Transforming Cloud ERP, Financial Systems, and Compliance Through Autonomous Multi-Agent Architectures
  Agentic AI adds another layer of governance risk‚ compliance obligations and auditability of enterprise financial applications․ Oracle Corporation sees agentic AI as the foundation of its enterprise applications strategy․ Beginning with embedded AI and task-ba…
  crossref Vijay Tiwari 2026-05-30T08:01:17Z 置信度 0.70
• Artificial superintelligence and its limits: why AlphaZero cannot become a general agent
  crossref Karim Jebari, Joakim Lundborg 2020-10-13T18:03:08Z 置信度 0.70
• CPU time slice allocation algorithm considering Agent deadline
  crossref Ai-zhen LIU 2008-12-12T05:35:05Z 置信度 0.70
• The Age of Autonomous Agents: A Bibliometric Review of Agentic AI Architectures, Applications, and Emerging Challenges
  The rapid evolution of large language models (LLMs) has catalyzed a shift from passive AI systems toward autonomous agentic architectures capable of reasoning, memory, tool use, and multi-agent collaboration. This bibliometric review characterizes the emerging…
  crossref Ben J. Weber, Clara M. Hofmann, Amara N. Okoye 2026-07-17T01:44:04Z 置信度 0.70
• Agentic Regulatory Intelligence: A Multi-agent AI Framework for Financial Crime Regulatory Pattern Monitoring and Guidance Generation
  Financial regulatory guidance for emerging criminal typologies reaches financial institutions through a slow, manual process that typically spans twelve to fifty-seven months after a new typology first appears in detection data. During that lag, criminal opera…
  crossref Nikhil Mittal 2026-08-07T06:22:18Z 置信度 0.70
• AI-Powered Talent Chain Management with Multi-Agent Systems for Industry and Innovation Growth
  Abstract This study introduces an innovative methodological framework for AI-driven talent chain management, addressing key challenges in workforce optimization, collaboration dynamics, and innovation assessment within complex and uncertain environments. Tradi…
  preprints Bin Wang, Juan Zhang 2026 置信度 0.74
• SORT-AI: Agentic System Stability in Large-Scale AI Systems Structural Causes of Cost, Instability, and Non-Determinism in Multi-Agent and Tool-Using Workflows
  The deployment of agentic AI systems—multi-agent orchestrations, tool-calling pipelines, and autonomous planning architectures—introduces operational instabilities that cannot be attributed to interconnect limitations or runtime control conflicts alone. Even i…
  crossref Gregor Herbert Wegener 2026-01-23T02:56:12Z 置信度 0.70
• Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings
  Building upon prior research that highlighted the need for standardizing environments for building control research, and inspired by recently introduced challenges for real life reinforcement learning (RL) control, here we propose a non-exhaustive set of nine …
  crossref Kingsley Nweye, Bo Liu, Peter Stone, Zoltan Nagy 2022-09-11T17:58:10Z 置信度 0.70
• The Evolution of Agentic AI in Cybersecurity: From Single LLM Reasoners to Multi-Agent Systems and Autonomous Pipelines
  Cybersecurity operations are increasingly adopting agentic AI solutions due to the time-critical and complex decision-making in security operations centers (SOCs). While large language models (LLMs) are good with summarization tasks or interpreting structured …
  crossref Vaishali Vinay 2026-02-23T20:46:21Z 置信度 0.70
• EAIF: An Enterprise AI Infrastructure Fabric for Trusted Multi-Agent Intelligence, Model Governance, and Autonomous Enterprise Operations
  Enterprises are moving from isolated machine-learning services toward agentic systems in which multiple models, tools, knowledge sources, and automation services collaborate to perform operational work. Existing enterprise AI platforms typically address model …
  crossref Naresh Somara 2026-08-25T08:18:51Z 置信度 0.70
• Multi-Agent MicroServices (MAMS)
  crossref Rem Collier, Katharine Beaumont, Eoin O'Neill 2026-06-19T08:54:02Z 置信度 0.70
• A New AI-Based Semantic Cyber Intelligence Agent
  The surge in cybercrime has emerged as a pressing concern in contemporary society due to its far-reaching financial, social, and psychological repercussions on individuals. Beyond inflicting monetary losses, cyber-attacks exert adverse effects on the social fa…
  crossref Fahim Sufi 2023-06-30T00:51:06Z 置信度 0.70
• Agricultural Futures Trading Decision Using AI Agent With Multiscale Candlestick Analysis_supp1-3583788.pdf
  crossref Jiaji Wu 2025-07-17T18:00:32Z 置信度 0.70
• Generative AI LLM agent preserve user privacy and safety
  crossref Debashish Roy, Mohammed Aliman, Rand Kouatly 2026-02-27T18:00:41Z 置信度 0.70
• Towards Coalition in a Multi-Agent Based Simulation for The Bomber Problem
  The Bomber Problem BP can be considered as a discrete time model in which a bomber must survive for t epochs before reaching the target where it will drop its bombs. The Bomber problem is unsolved despite his appearance date since the 1960s. It is classified i…
  crossref Boutheina Jlifi, Zina Elguedria, Khaled Ghedira 2014-06-01T17:15:21Z 置信度 0.70
• Robust Agent Compensation (RAC): Teaching AI Agents to Compensate
  We present Robust Agent Compensation (RAC), a log-based recovery paradigm (providing a safety net) implemented through an architectural extension that can be applied to most Agent frameworks to support reliable executions (avoiding unintended side effects). Us…
  crossref Srinath Perera, Kaviru Hapuarachchi, Frank Leymann, Rania Khalaf 2026-05-22T03:16:22Z 置信度 0.70
• Analyzing the Image Requirements for Dual-source Mobile AI Agent Assistants based on Female Perspective
  crossref Jingqi Yang, Huan Wang 2026-01-10T00:41:33Z 置信度 0.70
• Artificial intelligence as a discursive practice: the case of embodied software agent systems
  crossref Sean Zdenek 2004-03-18T20:59:06Z 置信度 0.70
• Designing AI Agent Workflows for Consumer Behavior Applications: A Practitioner's Framework
  The rapid advancement of large language model capabilities has created unprecedented opportunities for AI agent systems in consumer behavior applications, yet translating generic agent capabilities into production-ready business solutions remains challenging. …
  crossref Pratik Khedekar, Abhishek Vangipuram, Sravan Reddy Kathi 2026-02-08T10:12:38Z 置信度 0.70
• The Irreducible Moral Agent: Human Accountability and the Governance of AI-assisted Ethical Auditing after Arthur Andersen
  Artificial intelligence is increasingly presented as the technology that will finally purge fallible human judgment from the audit, and surpass humans in computational intelligence. 1 While the latter is indubitable, this article argues that the promise miscon…
  crossref Segun Ige 2026-08-18T08:13:27Z 置信度 0.70
• Agentic CDNs: A Multi-Agent Architecture for Edge-Native AI Inference and Control
  crossref Venkata Gopi Kolla, Chintan Tank, Luc Giavelli 2026-07-22T19:19:38Z 置信度 0.70
• AI Agent-Powered Fashion Shopping Services: A Future-Oriented Consumer Adoption Perspective
  crossref Yanbo Zhang, Chuanlan Liu 2026-07-01T16:50:54Z 置信度 0.70
• Generative AI as a Mediational Agent: Rethinking Learning in Sociocultural Theory
  Debates about the implications of generative AI in education largely frame AI as a tool—an extension of existing mediational means that support human activity. Drawing on sociocultural theory, we propose the alternate concept of mediational agent to describe a…
  crossref Tamara Powell Tate, Daniel Ritchie, mark warschauer uci 2026-04-25T05:58:15Z 置信度 0.70
• Verdict Fragility as a First-Class Output: Structured Reopen Conditions in Multi-Agent AI Deliberation
  Multi-agent AI deliberation systems produce verdicts that are necessarily snapshots: they reflect what the evidence establishes at the moment of deliberation. New data releases, regulatory decisions, experimental replications, and market events may all change …
  crossref Cory Kelly, Shubhanker Saxena 2026-07-18T00:18:58Z 置信度 0.70
• Value, Homo Economicus, and Agent-Based Modeling: The Importance of Re-Evaluating the Value Systems of AI
  As Machine Learning (ML) systems are becoming increasingly used and more complex, different value systems are being coded into Artificial Intelligence (AI). In this paper, we delineate the value systems that many AI systems hold and suggest alternative value f…
  crossref Ahan Devgun 2023-02-07T19:00:51Z 置信度 0.70
• Toward Agent-based Educational Science: Rethinking Educational Research in the Age of AI
  Educational science faces a structural mismatch between the pace of educational innovation and the methods used to evaluate its developmental impact. While new pedagogical approaches and AI-driven learning technologies are rapidly deployed, the empirical parad…
  crossref Yu Zhang, Jianxiao Jiang, Xin Tang 2026-02-12T20:08:13Z 置信度 0.70
• Directing the Machine: A Single-Case Study of Verification When an AI Agent Cannot Reach the Oracle
  AI coding agents now take on long, open-ended engineering work. Judging it is usually cheap: a compiler or test suite answers, and the agent runs the check itself. In other settings, correctness is settled only by a running system the agent can start but canno…
  crossref BATIN ÖRENE 2026-08-20T18:43:16Z 置信度 0.70
• Decision Science in the Agentic Era: Research Frontiers on Agentic AI and Human-Agent Collaboration
  Decision science is entering a new era in which decisions are no longer made solely by humans, but increasingly by autonomous AI agents and human-agent collectives. While prior research has largely treated AI as a tool for prediction or support, agentic system…
  crossref Yingjie Zhang, Tianshu Sun 2026-02-03T11:24:16Z 置信度 0.70
• Local Small LLM-based AI Agent System with Finite State Controller for SCADA Operation Assistance
  본 논문은 실제 지역난방 운영 현장에서 수집된 SCADA 데이터를 바탕으로 구성된 XAI4HEAT를 이용하여, 지역난방 운영 질의에 응답하는 로컬 소형 LLM 기반 AI agent 시스템을 제안한다. 지역난방 SCADA 질의응답은 운영자가 특정 시점 값, 기간 평균, 설비 간 비교 결과를 신속히 확인하는 실무와 직접 연결되므로, 자연스러운 문장 생성보다 정확한 절차 수행과 안전한 비응답이 더 중요하다. 기존의 종단 간(end-to-end) AI agent는 다음…
  crossref Jeong-Yoon Kim, Seung-Ho Lee 2026-08-27T01:25:16Z 置信度 0.70
• Organism Intelligence: First-Principles Design of Enterprise Organization, Agent Architecture, and Memory Systems in the AI Era
  <p>Despite massive capital investment, enterprise-level AI deployments are producing disappointing productivity returns. In our own initial deployment, using AI as an individual productivity tool produced only approximately 10% measured efficiency improv…
  crossref Hao Wu 2026-04-20T15:05:54Z 置信度 0.70
• Agent-Oriented Software Development: Building AI-Native Systems with JavaScript
  Agent-Oriented Software Development (AOSD) defines agent-based programming as the new standardfor software architecture that can harmonize deterministic legacy code with probabilistic AI-nativesoftware ecosystems. It is implemented as part of the JavaScript, T…
  crossref 2026-04-17T10:27:13Z 置信度 0.70
• Metacognitive Multi-Agent Framework for Preserving Critical Thinking in AI-Driven Education
  The rapid integration of Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) in higher education has dramatically boosted immediate student productivity but introduced severe concerns regarding systemic cognitive outsourcing. Traditiona…
  crossref Vedant Mhatre, Jai Desar, Aadi Singh Chauhan 2026-08-01T04:38:15Z 置信度 0.70
• The Human Tax: Agent Convergence and the Strategic Cost of Keeping Human Control in AI-Mediated Organizations
  Generative AI and agentic systems are moving into ordinary organizational work: marketing, product design, customer service, internal planning, hiring, analysis, and strategy. These systems offer speed and scale, but they also create a hidden strategic risk: a…
  crossref Kaleb Goessling 2026-07-29T06:21:53Z 置信度 0.70
• Agentic Leadership and the Limits of Scale: How Managing a Multi-Agent AI Ensemble Reveals New Theory
  Managing a heterogeneous multi-agent AI ensemble-where different agents bring distinct stylistic dispositions, calibration habits, and compliance tendencies-requires a form of human leadership competency that has no established name, no systematic theory, and …
  crossref Alfred Oldman 2026-07-29T13:23:44Z 置信度 0.70
• Generative Engine Optimization: A Three-Layer Semantic Framework for Content Visibility in AI-Powered Search
  The emergence of generative search engines (GES), including ChatGPT Search, Perplexity AI, and Google SGE, has transformed information retrieval by generating synthesized answers rather than ranked hyperlinks. Consequently, traditional Search Engine Optimizati…
  crossref Guruprasath Sankaran 2026-08-26T19:02:10Z 置信度 0.70
• Implementations, interpretative malleability, value-laden-ness and the moral significance of agent-based social simulations
  crossref Nuno David 2021-11-05T03:02:31Z 置信度 0.70
• Agent Trust Fabric: Graph-RAG Risk Reasoning for AI Agents, Wallets, and Marketing Campaigns
  The proliferation of autonomous AI agents operating across decentralised marketing ecosystems introduces a class of trust problems that conventional reputation systems are poorly equipped to handle. Static scoring, siloed behavioural records, and opaque risk s…
  crossref Ibtihajul Islam, Dr. Kashif Saleem 2026-03-18T18:19:02Z 置信度 0.70
• Distributed parking management architecture based on multi-agent systems
  <span>With the increase of the number of vehicles on the road, several traffic congestion problems arise in the big city, and this has a negative impact on the economy, environment and citizens. The time spent looking for a parking space and the traffic …
  crossref Nihal El Khalidi, Faouzia Benabbou, Nawal Sael 2021-10-26T09:41:15Z 置信度 0.70
• Conversational AI for multi-agent communication in Natural Language
  Research at the Interaction Lab focuses on human-agent communication using conversational Natural Language. The ultimate goal is to create systems where humans and AI agents (including embodied robots) can spontaneously form teams and coordinate shared tasks t…
  crossref Oliver Lemon 2022-09-16T13:46:04Z 置信度 0.70
• Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning
  The Lattice Boltzmann method (LBM) offers a powerful and versatile approach to simulating diverse hydrodynamic phenomena, spanning microfluidics to aerodynamics. The vast range of spatiotemporal scales inherent in these systems currently renders full resolutio…
  crossref Paul Fischer, Sebastian Kaltenbach, Sergey Litvinov, Sauro Succi 等 2026-07-25T12:08:31Z 置信度 0.70
• Automating the seismic-resilient design of fiber-reinforced concrete using a physics-informed multi-agent system
  The design of dynamically resilient concrete materials remains a complex, fragmented process that depends on iterative modelling, expert judgment, and poorly integrated workflows spanning structural analysis, material formulation, and seismic performance evalu…
  crossref Artem Zaitsev 2026-07-12T23:01:11Z 置信度 0.70
• Does Socialization Emerge in AI Agent Society? A Case Study of Moltbook
  As large language model agents increasingly populate networked environments, a fundamental question arises: do artificial intelligence (AI) agent societies undergo convergence dynamics similar to human social systems? Lately, Moltbook approximates a plausible …
  crossref Ming Li, Xirui Li, Tianyi Zhou 2026-05-22T03:16:22Z 置信度 0.70
• Agent‐Based Modeling and Simulation
  This article gives an introduction to agent‐based modeling and simulation (ABMS). After a general discussion about modeling and simulation, we address the basic concept of ABMS, focusing on its generative and bottom‐up nature, its advantages as well as its pit…
  crossref Franziska Klügl, Ana L. C. Bazzan 2017-07-18T00:33:50Z 置信度 0.70