List of Accepted Papers:
- A Toolchain to Design, Execute, and Monitor Robots Behaviors. Michele Colledanchise, Giuseppe Cicala, Daniele E. Domenichelli, Lorenzo Natale and Armando Tacchella
- Improving the Reliability of Service Robots by Symbolic Representation of Execution Specific Knowledge. Anastassia Küstenmacher and Paul Plöger
- Using Metareasoning to Maintain and Restore Safety for Reliably Autonomy. Justin Svegliato, Connor Basich, Sandhya Saisubramanian and Shlomo Zilberstein
- PEBL: Pessimistic Ensembles for Offline Deep Reinforcement Learning. Jordi Smit, Canmanie Ponnambalam, Matthijs Spaan and Frans Oliehoek
- Knowledge-based Sequential Decision Making under Uncertainty: A Survey. Shiqi Zhang and Mohan Sridharan
- Soft-Robust Algorithms for Batch Reinforcement Learning. Elita Lobo, Marek Petrik and Mohammad Ghavamzadeh
- Promoting Resilience of Multi-Agent Reinforcement Learning via Confusion-Based Communication. Ofir Abu, Sarah Keren, Jeffrey S. Rosenschein and Matthias Gerstgrasser
- Coyote: A Dataset of Challenging Scenarios in Visual Perception for Autonomous Vehicles. Suruchi Gupta, Ihsan Ullah and Michael Madden
- Towards Verification and Validation of Reinforcement Learning in Safety-Critical Systems: A Position Paper from the Aerospace Industry. Erik Nikko, Zoran Sjanic and Fredrik Heintz
- Mixed Observability MDPs for Shared Autonomywith Uncertain Human Behaviour. Clarissa Costen, Marc Rigter, Bruno Lacerda and Nick Hawes
- Planning with Inconsistent Sensory Feedback: Knowing When to Act Blind. Connor Basich, John Peterson and Shlomo Zilberstein
- Situation-Aware Task Planning for Robust AUV Explorations in Extreme Environments. Yaniel Carreno, Jonatan Scharff Willners, Yvan Petillot and Ron Petrick
- Planning to Avoid Side Effects (Preliminary Report). Toryn Q. Klassen and Sheila McIlraith
- Mission Planning in Unknown Environments as Bayesian Reinforcement Learning. Matthew Budd, Paul Duckworth, Nick Hawes and Bruno Lacerda