[CFP] Second call - European Workshop on Reinforcement Learning (EWRL 2022), September 19-21, Milan - Italy

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May 2, 2022, 10:47:45 AMMay 2
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CALL FOR PAPERS  (apologies for cross-postings, please forward to anybody who might be interested)

The 15th European Workshop on Reinforcement Learning (EWRL 2022) 


Dates:       19 September 2022 – 21 September 2022  

Location:    Aula De Carli - Politecnico di Milano - Campus Bovisa 

Via Candiani, 72 - 20158 - Milano (MI) - Italy 


We invite submissions for the 15th European Workshop on Reinforcement Learning (EWRL 2022) from the entire reinforcement learning spectrum. The papers can present new work or give a summary of the recent work of the author(s). There will be no proceedings of EWRL15. As such, papers that are intended for or have been submitted to other conferences or journals are also welcome. Submitted papers will be reviewed by the program committee in a double-blind procedure. All accepted papers will be considered for the poster sessions. Outstanding papers will also be considered for a 20 minutes oral presentation. 


Currently, we are planning on EWRL 2022 being a physical event. 


Important Dates 

  • Paper Submission Deadline: 1 June 2022 

  • Author Notification: 14 July 2022 

  • Camera Ready Sumbission: 1 September 2022 

The deadline on each of these dates is 23:59 (AoE). 



The 15th European Workshop on Reinforcement Learning (EWRL 2022) invites reinforcement learning researchers to participate in this new edition of this world-class event. We plan to make this an exciting event for researchers worldwide, not only for the presentation of top-quality papers but also as a forum for ample discussion of open problems and future research directions.  

Reinforcement learning is an active field of research that deals with the problem of sequential decision-making in unknown (and often) stochastic and/or partially observable environments. Recently there has been a wealth of both impressive empirical results as well as significant theoretical advances. Both types of advances are of significant importance, and we would like to create a forum to discuss such interesting results. 


The workshop will cover a range of sub-topics including (but not limited to): 

  • MDPs and Dynamic Programming 

  • Temporal Difference Methods 

  • Policy Optimization 

  • Model-based RL and Planning 

  • Exploration in RL 

  • Offline RL 

  • Unsupervised and Intrinsically Motivated RL 

  • Representation Learning in RL 

  • Lifelong and Non-stationary RL 

  • Hierarchical RL 

  • Partially Observable RL 

  • Multi-Agent RL 

  • Multi-Objective RL 

  • Transfer and Meta RL 

  • Deep RL 

  • Imitation Learning and Inverse RL 

  • Risk-sensitive and robust RL 

  • Theoretical aspects of RL 

  • Applications and Real-life RL 

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