In:
AI Communications, IOS Press, Vol. 35, No. 4 ( 2022-09-20), p. 357-368
Abstract:
The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Towards this goal, the Autonomous Agents Research Group develops novel machine learning algorithms for autonomous systems control, with a specific focus on deep reinforcement learning and multi-agent reinforcement learning. Research problems include scalable learning of coordinated agent policies and inter-agent communication; reasoning about the behaviours, goals, and composition of other agents from limited observations; and sample-efficient learning based on intrinsic motivation, curriculum learning, causal inference, and representation learning. This article provides a broad overview of the ongoing research portfolio of the group and discusses open problems for future directions.
Type of Medium:
Online Resource
ISSN:
1875-8452
,
0921-7126
Language:
Unknown
Publisher:
IOS Press
Publication Date:
2022
detail.hit.zdb_id:
2036677-2
detail.hit.zdb_id:
740533-9
Bookmarklink