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CORDIS - Resultados de investigaciones de la UE
CORDIS

Multi-Agent Systems for Pervasive Artificial Intelligence for assisting Humans in Modular Production Environments

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Report on the standardization landscape and applicable standards (se abrirá en una nueva ventana)

A report containing the standards relevant for the project as starting material and the relevant standardization committees

Smart Factory testbed setup - Final results (se abrirá en una nueva ventana)

This deliverable will describe the final results of the testbed setup of T61

Implementation of knowledge models (se abrirá en una nueva ventana)

A document that describes all formalized knowledge models for all use cases representing relevant domain knowledge on processes products human worker etc

Use cases requirements and specifications (se abrirá en una nueva ventana)

Report describing the use case requirements and specifications as well as the KPIs targets and baselines for all indicators

Standardisation proposals (se abrirá en una nueva ventana)

Report that suggests parts of MAS4AI specifications that could become part of the formal standard

Intelligent Multi-agent System Architecture (se abrirá en una nueva ventana)

The RAMI40 based reference architecture and specifications for the MAS4AI system

User manuals on accessing and using the MAS (se abrirá en una nueva ventana)

Report containing user manuals that describe how the multiagentsystem and basic AI agents can be utilized

Report on the contribution to standardization (se abrirá en una nueva ventana)

Report describing MAS4AI interaction with the relevant standardization committees and the contribution achieved to the development of standards based in the project results

Dissemination & communication activities - Third version (se abrirá en una nueva ventana)

Final report on dissemination and communication activities including the impact assessment and KPIs attainment analysis

Modelling of the planning agent (se abrirá en una nueva ventana)

This deliverable will provide the design consideration of the hierarchical planning agent

Lessons learnt and recommendations for instantiation of AI technologies in manufacturing (se abrirá en una nueva ventana)

This report will describe the lessons learnt and provide recommendations for AI in manufacturing

Smart Factory testbed setup - Initial results (se abrirá en una nueva ventana)

This deliverable will describe the initial results of the testbed setup of T61

User manuals on agent configuration and execution (se abrirá en una nueva ventana)

Report containing user manuals that describe how agents can be configured with the Agent Service Description and how to execute Agents

Dissemination & communication activities - Initial version (se abrirá en una nueva ventana)

The document presenting the plan of dissemination communication activities to be followed by the consortium Detailed planning for the first 18 month with dissemination and communication targets and KPIs for the entire project

Final Public Report (se abrirá en una nueva ventana)

The public report summarising the major project results and highlights. Includes also an analytical assessment of the delivered impacts.

Ethics framework (se abrirá en una nueva ventana)

report detailing the proposed ethics framework taking into account legal and privacy aspects of AI deployment in the pilots

Dissemination & communication activities - Second version (se abrirá en una nueva ventana)

Updated plan of dissemination communication activities to be followed by the consortium Includes the report on the dissemination and communication activities carried out by the consortium to date

System requirements (se abrirá en una nueva ventana)

Report describing the MAS4AI system requirements for the industrial cases

Demonstrator execution - Initial results (se abrirá en una nueva ventana)

This deliverable will describe the initial results of the demonstrators of T6.2 to T6.6

Development of the planning agent (se abrirá en una nueva ventana)

The final prototype of the planning agent and a short accompanying report detailing the development activities

Integration of knowledge representation (se abrirá en una nueva ventana)

A prototype accompanied by a report that details the agent knowledge system as part of the integration of agent technologies in WP3, WP4, WP5.

Agent knowledge access framework (se abrirá en una nueva ventana)

The prototype of a generic agent access system that provides access to the knowledge of the agent including semantic logic This prototype will be accompanied by a short report

Demonstrator execution - Final results (se abrirá en una nueva ventana)

This deliverable will describe the final results of the demonstrators of T6.2 to T6.6

Hierarchical planning agent integration (se abrirá en una nueva ventana)

This deliverable will handle the integration of the hierarchical planning agent to the MAS4AI system. A prototype of the integrated planning agent will be provided accompanied by a report.

Data Management Plan (se abrirá en una nueva ventana)

The document describing the principles and procedures of handling projects research data by the consortium

Public web portal (se abrirá en una nueva ventana)

Public site of the project accessible by all audiences for promoting the dissemination and communication activities

Publicaciones

Enabling a Multi-Agent System for Resilient Production Flow in Modular Production Systems (se abrirá en una nueva ventana)

Autores: Simon Komesker, William Motsch, Jens Popper, Aleksandr Sidorenko, Achim Wagner, Martin Ruskowski
Publicado en: 2022
Editor: Elsevier
DOI: 10.1016/j.procir.2022.05.097

A toolbox of agents for scheduling the paint shop in bicycle industry (se abrirá en una nueva ventana)

Autores: Siatras Vasilis, Nikolakis Nikos, Alexopoulos Kosmas, Mourtzis Dimitris
Publicado en: 2022
Editor: Elsevier
DOI: 10.1016/j.procir.2022.05.124

Simultaneous Production and AGV Scheduling using Multi-Agent Deep Reinforcement Learning (se abrirá en una nueva ventana)

Autores: Jens Popper, Vassilios Yfantis, Martin Ruskowski
Publicado en: 2021
Editor: Elsevier
DOI: 10.1016/j.procir.2021.11.257

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