ΑΙhub.org
 

Conference on Reinforcement Learning and Decision Making

by
05 July 2022



share this:

The 5th Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM) 2022 took place at Brown University from 8-11 June. The programme included invited and contributed talks, workshops, and poster sessions. The goal of RLDM is to provide a platform for communication among all researchers interested in learning and decision making over time to achieve a goal.

Over the last few decades, reinforcement learning and decision making have been the focus of an incredible wealth of research spanning a wide variety of fields including psychology, artificial intelligence, machine learning, operations research, control theory, neuroscience, economics and ethology. The interdisciplinary sharing of ideas has been key to many developments in the field, and the meeting is characterized by the multidisciplinarity of the presenters and attendees.

Michael Littman (one of the conference general chairs) said that the conference had been a great success, both in terms of the organization and the content: “For many of us, it was the first in-person conference since the start of the pandemic. The organizers put a lot of thought into ways of keeping people safe from COVID and it appears to have paid off, with very few attendees testing positive. RLDM is always exciting, in part because of the effort to coordinate between the cognitive/neuroscience researchers studying decision-making in natural systems and the AI/ML researchers looking at decision-making in machines”.

RLDM lecture theatreOne of the speakers at RLDM. Photo credit: Michael J Frank.

Watch the recordings of the talks

The talks from the four days of the conference were recorded, and you can watch them here:
Day 1 | Day 2 | Day 3 | Day 4

The talks are also available split by individual speakers here.

Best paper awards

Two articles received the honour of RLDM 2022 Best Paper Award:

  • Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik Learned-Miller, Emma Brunskill, Philip S. Thomas, Universal off-policy evaluation.
  • Diksha Gupta, Brian DePasquale, Charles Kopec, Carlos Brod, An explanatory link between history biases and lapses.

Some of the participants shared their experience on Twitter.

The event website is here.




Lucy Smith , Managing Editor for AIhub.
Lucy Smith , Managing Editor for AIhub.




            AIhub is supported by:


Related posts :



Learning programs with numerical reasoning

Introducing a novel approach to efficiently learning programs with numerical values
13 June 2024, by

Interview with Tianfu Wang: A reinforcement learning framework for network resource allocation

Addressing resource allocation problems in the domain of network virtualization.
12 June 2024, by

Congratulations to the #IJCAI2024 award winners

The winners of three prestigious IJCAI awards for 2024 have been announced.
11 June 2024, by

Forthcoming machine learning and AI seminars: June 2024 edition

A list of free-to-attend AI-related seminars that are scheduled to take place between 10 June and 31 July 2024.
10 June 2024, by

Tweet round-up from #ICWSM24

Find out what participants got up to at the International Conference on Web and Social Media
10 June 2024, by

Interview with AAAI Fellow Mausam: talking information extraction, mentorship, and creativity

We spoke to Professor Mausam about his research, career path, and being selected as a 2024 AAAI Fellow.
06 June 2024, by




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association