{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T07:03:38Z","timestamp":1782975818442,"version":"3.54.5"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:00:00Z","timestamp":1780358400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:00:00Z","timestamp":1780358400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,2]]},"DOI":"10.1109\/eucnc\/6gsummit68295.2026.11577580","type":"proceedings-article","created":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T19:34:25Z","timestamp":1782934465000},"page":"163-170","source":"Crossref","is-referenced-by-count":0,"title":["Pyomnet-AI: Enabling Efficient Omnet\u00b2\u00b2 Network Optimization Through Low-Overhead, Hybrid Python AI Integration"],"prefix":"10.1109","author":[{"given":"Moustafa","family":"Roshdi","sequence":"first","affiliation":[{"name":"Fraunhofer Institute for Integrated Circuits IIS,Erlangen,Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arindam","family":"Chakraborty","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute for Integrated Circuits IIS,Erlangen,Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amir","family":"Amri","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute for Integrated Circuits IIS,Erlangen,Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sahana","family":"Raghunandan","sequence":"additional","affiliation":[{"name":"Fraunhofer Institute for Integrated Circuits IIS,Erlangen,Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reinhard","family":"German","sequence":"additional","affiliation":[{"name":"Friedrich-Alexander University (FAU),Erlangen-Nuremberg,Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2924243"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3384460"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.001.1900287"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000195"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.softx.2023.101320"},{"key":"ref6","author":"Stolpmann","year":"2024","journal-title":"omnetpp-ml: Machine Learning in OMNeT++. GitHub repository. Repository last updated Jan 26, 2024 (per GitHub). ComNetsHH (Institute of Communication Networks, Hamburg University of Technology)"},{"key":"ref7","article-title":"Gymnasium: A Standard Interface for Reinforcement Learning Environments","volume-title":"The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track","author":"Towers","year":"2025"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/VNC51378.2020.9318324"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3389400.3389404"},{"key":"ref10","article-title":"OpenAI Gym","author":"Brockman","year":"2016","journal-title":"arXiv preprint"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3345768.3355908"},{"key":"ref12","volume-title":"Omnetpy: using Python to write OMNeT++ simulations","author":"Modenesi"},{"key":"ref13","article-title":"System Level Simulator for 3D Mobile Networks","volume-title":"12th Advanced Satellite Multimedia Systems Conference and the 18th Signal Processing for Space Communications Workshop (ASMS\/SPSC)","author":"Roshdi"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOMWKSHPS61880.2024.10620834"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.23919\/WMNC53478.2021.9619001"},{"key":"ref16","volume-title":"Tensorforce. Tensorforce: a TensorFlow library for applied reinforcement learning"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/WSA65299.2025.11202782"}],"event":{"name":"2026 Joint European Conference on Networks and Communications &amp; 6G Summit (EuCNC\/6G Summit)","location":"M\u00e1laga, Spain","start":{"date-parts":[[2026,6,2]]},"end":{"date-parts":[[2026,6,5]]}},"container-title":["2026 Joint European Conference on Networks and Communications &amp;amp; 6G Summit (EuCNC\/6G Summit)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11577191\/11577118\/11577580.pdf?arnumber=11577580","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T05:44:40Z","timestamp":1782971080000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11577580\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,2]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/eucnc\/6gsummit68295.2026.11577580","relation":{},"subject":[],"published":{"date-parts":[[2026,6,2]]}}}