Conference item
On-the-fly strategy adaptation for ad-hoc agent coordination
- Abstract:
-
Training agents in cooperative settings offers the promise of AI agents able to interact effectively with humans (and other agents) in the real world. Multi-agent reinforcement learning (MARL) has the potential to achieve this goal, demonstrating success in a series of challenging problems. However, whilst these advances are significant, the vast majority of focus has been on the self-play paradigm. This often results in a coordination problem, caused by agents learning to make use of arbitra...
Expand abstract
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Authors
Bibliographic Details
- Publisher:
- International Foundation for Autonomous Agents and Multiagent Systems Publisher's website
- Host title:
- AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems
- Pages:
- 1771-1773
- Publication date:
- 2022-05-09
- Acceptance date:
- 2021-12-20
- Event title:
- 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022)
- Event location:
- Auckland, New Zealand
- Event start date:
- 2022-05-09
- Event end date:
- 2022-05-13
- DOI:
- EISSN:
-
1558-2914
- ISSN:
-
1548-8403
- ISBN:
- 9781450392136
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1272851
- Local pid:
- pubs:1272851
- Deposit date:
- 2023-01-20
Terms of use
- Copyright holder:
- International Foundation for Autonomous Agents and Multiagent Systems
- Copyright date:
- 2022
- Rights statement:
- © 2022 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
- Notes:
- This is the accepted manuscript version of the paper. The final version is available online from the International Foundation for Autonomous Agents and Multiagent Systems at: https://doi.org/10.5555/3535850.3536105
Metrics
If you are the owner of this record, you can report an update to it here: Report update to this record