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RL4PROD 2023 : AAAI 2023 Reinforcement Learning Ready for Production Workshop


When Feb 13, 2023 - Feb 14, 2023
Where Washington, DC
Submission Deadline TBD
Categories    reinforcement learning   artificial intelligence   machine learning

Call For Papers

* Description of workshop: The 1st Reinforcement Learning Ready for Production workshop, held at AAAI 2023, focuses on understanding reinforcement learning trends and algorithmic developments that bridge the gap between theoretical reinforcement learning and production environments.

* Topics:
• Efficient reinforcement learning algorithms that optimize sample complexity in real-world environments
• Counterfactual evaluation for reinforcement learning algorithms
• Reinforcement learning research for Recommendation Systems, Robotics, Optimization and many more industry fields that enables productionalization of reinforcement learning.
• Novel applications for reinforcement learning in the internet, robotics, chip design, supply chain and many more industry fields. Outcomes from these applications should come from either production environments or well-recognized high-fidelity simulators (excluding standard OpenAI Gym and standard Atari Games)

* Format of workshop: This workshop will be a 1 day workshop. We have confirmed 7 distinguished reinforcement learning researchers and practitioners to speak or participate in panel for this workshop (listed in the next section, some have scheduling pending). We will have a reinforcement learning foundations panel, and talks on reinforcement learning advancements, applications in recommender systems, robotics, medical systems, and production A/B experiments. We anticipate about 4 hours of hosted content from the workshop and 1.5 hours of poster sessions and 1.5 hours of contributed talks, which will go from 10 am to 5 pm on the workshop day. Each talk or panel will be 40 minutes of content with 10 minutes of Q\&A session.

* Attendance: We expect to invite people who have their paper accepted and industry/academia experts familiar with this matter.

* Submission requirements: We expect 6-8 pages for full papers excluding reference and supplement.

* Submit to:


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