Connectionists: Deadline extension: IEEE ICDL Workshop on Human-aligned Reinforcement Learning for Autonomous Agents and Robots

[Francisco Cruz]

Call for Papers: IEEE ICDL 2021 Workshop:
Human-aligned Reinforcement Learning for Autonomous Agents and Robots
Website: https://harlworkshop.github.io/
Virtual conference
Date: August 27th, 2021

**Submission Deadline extended to: July 12th, 2021 (11:59pm AOE)**
**We particularly encourage authors to share their in-progress works
in the form of extended abstracts and short papers.**

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**Call for Papers:**

We invite researchers from the reinforcement learning and robotics
community to submit their recent works pertaining to the issue of
incorporating human-related aspects into (deep) reinforcement learning
agents and robots.

The focus of this workshop is to bring together researchers from the
fields of robotics and reinforcement learning to discuss and share
state-of-the-art methods, challenges and novel solutions pertaining to
the issue of incorporating human-related aspects into reinforcement
learning agents and robots. We hope to provide an opportunity to
discuss fundamental, current issues and future research directions to
foster the presence of autonomous agents and robots in real-world
scenarios. The main topics of interest are explainability,
interactivity, safety, and ethics in social robotics and autonomous
agents especially from a reinforcement learning perspective. In this
regard, approaches with special interest for this workshop are (but
not limited to):

- Explainability, interpretability, and transparency methods for
feature-oriented and goal-driven RL
- Explainable robotic systems with RL approaches
- Assisted and interactive RL in human-robot and human-agent scenarios
- Human-in-the-loop RL and applications
- RL from demonstrations and imperfect demonstrations
- Robot and agent learning from multiple human sources
- Multi-robot systems with human collaboration
- Safe exploration during learning
- Ethical reasoning and moral uncertainty
- Fairness in RL and multi-agent systems
- Theory of mind based RL frameworks
- Use of human priors in RL

We invite submissions of both extended abstracts (upto 2 pages
including references) as well as full papers (upto 6 pages including
references). Submissions must be in PDF, formatted using the IEEE
conference style in two columns. PDF manuscripts may be submitted
through EasyChair.

Selected contributions will be presented during the workshop as
spotlight talks and in a poster session. Accepted papers will be
uploaded to the workshop website, but are free to appear in other
journals or conference proceedings.

Contributors to the workshop will be invited to submit extended
versions of the manuscripts to a topical collection (special issue) at
Neural Computing and Applications.


**Key Dates:**

Submission Deadline: July 12, 2021 (11:59pm AOE) (EXTENDED)
Acceptance Notification: July 30, 2021
Camera-ready version: August 12, 2021 (11:59pm AOE)
Workshop: August 27 (Tentative), 2021


**Confirmed list of Speakers:**

- Matthew Taylor, University of Alberta, Canada.
- Alessandra Sciutti, IIT, Italy.
- Stefan Wermter, University of Hamburg, Germany.
- Peter Vamplew, Federation University, Australia.
- Bradley Knox, Bosch, USA.
- Benjamin Rosman, University of the Witwatersrand, South Africa.
- Felipe Leno da Silva, São Paulo State University UNESP, Brazil.
- Jens Kober, Delft University of Technology, The Netherlands.
- Bruno Fernandes, University of Pernambuco, Brazil.
- Nicolas Navarro-Guerrero, Aarhus University, Denmark.
- George Konidaris, Brown University, USA.
- Richard Dazeley, Deakin University, Australia.


**Organizers:**

Francisco Cruz (School of Information Technology, Deakin University, Australia)
Thommen George Karimpanal (Applied Artificial Intelligence Institute,
Deakin University, Australia)
Miguel Solis (Facultad de Ingeniería, Universidad Andrés Bello, Chile)
Pablo Barros (Cognitive Architecture for Collaborative Technologies
Unit, Istituto Italiano di Tecnologia, Italy)
Richard Dazeley (Machine Intelligence Lab, Deakin University, Australia)