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Dernières publications et brevets sur l'IA agentique

Agent IA

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Vous êtes un agent.
L'intelligence artificielle révolutionne conception de produits en permettant une prise de décision autonome et axée sur les objectifs grâce à des processus itératifs.

L'IA agentique désigne les systèmes d'IA qui poursuivent des objectifs en plusieurs étapes de manière autonome en itérant à travers des boucles de perception, de planification, d'utilisation d'outils et d'auto-correction sans nécessiter d'intervention humaine à chaque point de décision — une rupture structurelle avec les modèles de réponse instantanée à un seul tour vers des architectures qui décomposent les objectifs complexes en sous-tâches, exécutent des actions sur des environnements externes, évaluent les résultats et révisent les plans en conséquence.

L'architecture agentique canonique associe un grand modèle linguistique de raisonnement à un registre d'outils - navigateurs web, interprètes de code, clients API, systèmes de fichiers, interfaces de base de données - et à une architecture de mémoire couvrant le contexte de travail à court terme, les enregistrements épisodiques des actions passées et les connaissances à long terme récupérées, ce qui permet à l'agent de poursuivre des objectifs cohérents sur des horizons d'interaction étendus qui dépassent toute fenêtre de contexte unique. Les configurations multi-agents vont plus loin, distribuant les sous-tâches à des agents spécialisés coordonnés par un orchestrateur, introduisant des fonctions inter-agents, des fonctions de gestion de l'information, des fonctions de gestion de l'information et des fonctions de gestion de l'information. communication les protocoles, l'agrégation des résultats et la résolution des conflits sont des préoccupations architecturales supplémentaires.

Les publications et brevets indexés ci-dessous traitent des algorithmes de planification, des architectures d'utilisation d'outils, des systèmes de mémoire, des protocoles de coordination multi-agents, des bancs d'essai d'évaluation d'agents et des méthodologies de contraintes de sécurité.

Voici notre dernière sélection de publications et de brevets mondiaux en anglais sur l'IA agentique, parmi de nombreuses revues scientifiques en ligne, classées et axées sur l'IA agentique, l'agent d'IA, l'agent d'IA autonome, le système multi-agent, l'orchestration de l'agent d'IA, la boucle de planification de l'agent, l'agent ReAct, la planification de la chaîne de pensée, l'agent d'IA utilisant des outils, l'appel de fonction à l'IA, la mémoire de l'agent d'IA, la mémoire à long terme de l'agent, la mémoire épisodique de l'agent, mémoire de travail de l'agent, décomposition des tâches de l'agent d'IA, planification hiérarchique de l'agent, autocorrection de l'agent d'IA, réflexion de l'agent d'IA, évaluation de l'agent d'IA, mise en forme de la récompense de l'agent, bac à sable de l'agent d'IA, garde-fous de sécurité de l'agent, coordination multi-agent, protocole de communication de l'agent, registre des outils de l'agent d'IA, agent exécutant le code, agent navigant sur le web, agent augmenté par la recherche, évaluation de référence de l'agent et agent humain dans la boucle.

Method for performing a task according to a flare model including a multi-modal planning module and an environment-adaptive replanning module and ai a

Patent published on the 2026-05-21 in US under Ref US20260141703 by UIF UNIV INDUSTRY FOUNDATION YONSEI UNIV [KR] (Kim Tae Woong [kr], Kim Byeonghwi [kr], Choi Jonghyun [kr])

Abstract: [0000] A method for performing a task according a FLARE model including a multi-modal planning module and an environment-adaptive replanning module is provided. The method of an AI agent includes steps of: (a) instructing the multi-modal planning module to calculate degrees of similarity between training data and a current pair comprised of natural language data and image data and acquire k natural language data by using the degrees of similarity; (b) instructing the multi-modal planning module [...]


Our summary: The method involves an AI agent utilizing a multi-modal planning module to analyze natural language and image data. It generates an initial action plan based on similarity degrees and adapts the plan using an environment-adaptive replanning module when necessary. The process ensures effective task performance even when target information is incomplete.

AI, multi-modal planning, environment-adaptive replanning, FLARE model

Patent

Computer-implemented method, computer system, data models, and computer program for simulating degradation, ageing, performance, and/or thermal behavi

Patent published on the 2026-05-20 in EP under Ref EP4745825 by BATTERY SPHERE GMBH [DE] (Lutz Lukas [de], Scherrer Luca [de], Alves Dalla Corte Daniel [de], Principe Victor [de])

Abstract: [0001] The invention relates to a computer-implemented method for simulating and predicting a degradation, ageing, performance, and/or thermal behavior of an electric battery, a method for generating corresponding training datasets, and a computer system for supporting users in different aspects of battery development, testing and validation. This battery domain specific artificial intelligence system (Battery AI System) applies raw data preparation steps like segmenting, timestamp data extracti[...]


Our summary: The invention describes a method and system for simulating battery degradation and performance. It utilizes transformer-based machine learning models for accurate predictions. A large language model facilitates user interaction with the Battery AI System.

simulation, battery, machine learning, degradation

Patent

Dynamic navigation generation using ai

Patent published on the 2026-05-07 in US under Ref US20260126295 by IBM [US] (Brew Kevin Wayne [us], Shah Priti Ashvin [us], Morillo Jaime D [us])

Abstract: [0000] A monitoring system includes a computer hardware system with a hardware processor configured to initiate the following executable operations. Communications from one or more communication devices associated with first responders are real-time monitored. Using an artificial intelligence (AI) agent analyzing the communications, an event is detected. Using the AI agent, an event location associated with the event is identified. Using the AI agent and the event location, an occlusion zone ass[...]


Our summary: The system monitors real-time communications from first responders. An AI agent detects events and identifies their locations. It generates occlusion zones and updates map data for route adjustments.

AI, dynamic navigation, event detection, occlusion zone

Patent

Adaptive ai coworker for organizational operations

Patent published on the 2026-05-07 in US under Ref US20260127021 by LUMINADATA INC [US] (Chafekar Deepti [us], Ara Afrozy [us])

Abstract: [0000] Examples relate to an adaptive AI coworker system for enhancing organizational operations. The system generates personalized AI coworkers based on role requirements, employing adaptive learning to understand unique organizational practices. It utilizes multi-agent coordination for complex task execution, automatically generating, prioritizing, and allocating tasks based on organizational context. The system integrates data from various sources, implementing data governance measures. Custo[...]


Our summary: The system generates personalized AI coworkers tailored to role requirements. It employs adaptive learning and multi-agent coordination for efficient task execution. Explainable AI features ensure transparency and compliance with data governance standards.

adaptive AI, organizational operations, multi-agent coordination, explainable AI

Patent

Computer-implementable method and system for document-based question answering

Patent published on the 2026-04-22 in EP under Ref EP4730150 by KONINKLIJKE PHILIPS NV [NL] (Eisenhardt Marc [nl])

Abstract: The present invention relates to a system and computer-implementable method for document-based question answering. The method comprises obtaining a document; obtaining a question of a user related to said document; invoking an AI agent to generate an answer to said question; and outputting the generated answer.[...]


Our summary: The invention provides a method for answering questions based on documents. It involves obtaining a document and a user question. An AI agent generates and outputs the answer to the question.

document-based QA, AI agent, question answering, computer-implementable method

Patent

Multi-agent process simulations

Patent published on the 2026-04-22 in EP under Ref EP4730201 by SAP SE [DE] (Gerber Andreas [de])

Abstract: [0001] Systems and methods described herein provide a computer-implemented approach for process simulations using multi-agent systems. Software agents are trained using historical process data associated with a process. Each software agent represents a single task in the process. Based on a candidate process model, the process is simulated to generate simulation results by executing a multi-agent system. The software agents operate autonomously within the multi-agent system based on trained beha[...]


Our summary: This content describes a method for simulating processes using multi-agent systems. Software agents are trained on historical data to represent tasks within the process. The simulation results are compared with runtime results to adjust the process model iteratively.

multi-agent systems, process simulation, software agents, runtime configuration

Patent

agentic AI and the future of electron microscopy

Published on 2026-04-10 by Vida Jamali, Amirali Aghazadeh, Josh Kacher @NATURE npj

Abstract: npj Computational Materials, Published online: 10 April 2026; doi:10.1038/s41524-026-02077-yAdvances in microscopy have long focused on improving resolution, throughput, and automation. The next transformation may lie in enabling microscopes to contribute to the reasoning that guides experiments. Recent advances in agentic artificial intelligence (AI) suggest a future in which microscopes do more than simply acquire images. Agentic systems could draw on prior knowledge, interpret experimental ou[...]


Our summary: Advances in agentic AI could enable electron microscopes to interpret data and design experiments. This transformation may shift microscopes from passive tools to active collaborators in research. The transition requires community support through open access and data sharing initiatives.

agentic AI, electron microscopy, experimental design, materials characterization

Publication

A Scoping Review

Published on 2026-02-01 by Jonathan Gibson, Praveen Chinniah, Shashank Chapala, Ojasvi Vemuri, Rajesh Botchu @MDPI

Abstract: Objectives: Artificial intelligence (AI) is a transformative development in the field of medicine. In the field of musculoskeletal radiology, agentic AI is a technology that could flourish, but currently, the limited evidence base is fragmented and sparse, and we present a scoping review of it. Methods: Parallel searches were conducted in four databases: PubMed, Embase, Scopus, and Web of Science. Search terms included all agentic AI and autonomous AI agents, as well as radiology. All papers und[...]


Our summary: This scoping review evaluates the potential of agentic AI in musculoskeletal radiology. It identifies eleven relevant studies highlighting improved decision support, workflow optimization, and image analysis. Despite promising findings, the evidence base remains limited and theoretical.

AI in Radiology, Musculoskeletal Imaging, Workflow Optimization, Decision Support

Publication

Sujets abordés : IA agentique, prise de décision autonome, processus itératifs, objectifs à plusieurs étapes, perception, planification, utilisation d'outils, boucles d'autocorrection, grand modèle de langage, architecture de mémoire, configurations multi-agents, protocoles de communication inter-agents, algorithmes de planification, critères d'évaluation des agents, méthodologies des contraintes de sécurité, résolution de conflits, orchestrateur ISO/IEC 27001, ISO/IEC 25010, ISO 9241, ISO/IEC 2382, et IEEE 1012.

Glossaire des termes utilisés

Application Programming Interface (API): un ensemble de règles et de protocoles qui permet à différentes applications logicielles de communiquer et d'interagir entre elles, permettant l'intégration de fonctionnalités et l'échange de données entre les systèmes.

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