Authors: Ahmed, Ibrahim H. | Brewitt, Cillian | Carlucho, Ignacio | Christianos, Filippos | Dunion, Mhairi | Fosong, Elliot | Garcin, Samuel | Guo, Shangmin | Gyevnar, Balint | McInroe, Trevor | Papoudakis, Georgios | Rahman, Arrasy | Schäfer, Lukas | Tamborski, Massimiliano | Vecchio, Giuseppe | Wang, Cheng | Albrecht, Stefano V.
Article Type:
Research Article
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.
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Keywords: Deep reinforcement learning, multi-agent reinforcement learning, ad hoc teamwork, agent/opponent modelling, goal recognition, autonomous driving, multi-robot warehouse
DOI: 10.3233/AIC-220116
Citation: AI Communications,
vol. 35, no. 4, pp. 357-368, 2022
Price: EUR 27.50