Call for Papers |
|
The 1st edition of RECON - Reinforcement Learning for Communication and Network Optimization workshop, co-located with the IEEE Military Communications Conference (MILCOM 2023)
30 October – 3 November 2023 // Boston, MA, USA https://milcom2023.milcom.org. Scope and topics RECON focuses on the application of Reinforcement Learning (RL) to tactical and civilian communication networks. RECON aims to cover a wide range of topics within this domain, and we encourage researchers to submit their work on various subjects including, but not limited to, network planning, network optimization, adaptive protocols, decentralized network management, novel learning algorithms and frameworks, agent coordination architectures, datasets and testbeds, and practical challenges associated with deploying RL and Machine Learning (ML) in communication networks. For more information and submission details, please visit the MILCOM 2023 website at https://milcom2023.milcom.org. Topics • General topics: – (Central / Distributed) Network planning – Network optimization (combinatorial and learned) – RL, MARL, Deep Learning techniques – Ad-hoc adaptive protocols – Practical challenges for deploying ML solutions into real-networks – Distributed Learning paradigms (Distributed learning architecture, Federated Learning) – Deep Learning architectures and solutions suitable to process networking information/scenarios (GNNs, Transformers, Autoencoders) • Single and Multi-Agent Reinforcement Learning – Communication protocol optimization – Decentralized network management – Data Management – Agent(s) coordination architectures suitable to DIL networks – Learning to Communicate – Self-driving networks – Custom RL training environments – Cross-Layer routing – Exploration techniques • Machine Learning for Network Analysis – Network state prediction and estimation – ML for configuration parameters identification – Traffic analysis – Intrusion detection – Anomaly detection – ML at the network edge (Edge ML) • Testsbeds and Datasets – Testbeds and architectures – Datasets – Generation of mobility patterns/scenarios – Data validation techniques – Datasets for Offline RL Organizing Committee Raffaele Galliera, University of West Florida, Florida, USA, [email protected] Thies Mohlenhof, Fraunhofer-Gesellschaft FKIE, Germany, [email protected] Filippo Poltronieri, University of Ferrara, Italy, [email protected] Important Dates • Submission Deadline: 4 September 2023 • Notification of Acceptance: 18 September 2023 Submission instructions All submissions should be written in English with draft papers up to six (6) printed pages in length, two-column, single-spaced with 10-point font on US Letter paper. Final papers that exceed six (6) pages will be assessed a per-page over-length charge of $150/page, up to a maximum of eight (8) total pages. Please check the manuscript requirements for further details. Submission link: https://edas.info/N31310 |
Summary |
|
RECON 2023 : The 1st edition of RECON - Reinforcement Learning for Communication and Network Optimization workshop will take place in Boston, MA, USA. It’s a 5 days event starting on Oct 30, 2023 (Monday) and will be winded up on Nov 3, 2023 (Friday). RECON 2023 falls under the following areas: REINFORCEMENT LEARNING, TACTICAL NETWORKS, MACHINE LEARNING, etc. Submissions for this Workshop can be made by Sep 4, 2023. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the RECON 2023
|
Credits and Sources |
| [1] RECON 2023 : The 1st edition of RECON - Reinforcement Learning for Communication and Network Optimization workshop |
