2 citations · 3 across the 11 of their papers we have counts for
5 papers · 1 filter
Opportunities of Reinforcement Learning in South Africa's Just Transition
Claude Formanek, Callum Rhys Tilbury, Jonathan P. Shock
South Africa stands at a crucial juncture, grappling with interwoven socio-economic challenges such as poverty, inequality, unemployment, and the looming climate crisis. The govern…
Multi-Agent Reinforcement Learning with Selective State-Space Models
Jemma Daniel, Ruan de Kock, Louay Ben Nessir +5
The Transformer model has demonstrated success across a wide range of domains, including in Multi-Agent Reinforcement Learning (MARL) where the Multi-Agent Transformer (MAT) has em…
Putting Data at the Centre of Offline Multi-Agent Reinforcement Learning
Claude Formanek, Louise Beyers, Callum Rhys Tilbury +2
Offline multi-agent reinforcement learning (MARL) is an exciting direction of research that uses static datasets to find optimal control policies for multi-agent systems. Though th…
Coordination Failure in Cooperative Offline MARL
Callum Rhys Tilbury, Claude Formanek, Louise Beyers +2
Offline multi-agent reinforcement learning (MARL) leverages static datasets of experience to learn optimal multi-agent control. However, learning from static data presents several…
Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation
Claude Formanek, Callum Rhys Tilbury, Louise Beyers +2
Offline multi-agent reinforcement learning (MARL) is an emerging field with great promise for real-world applications. Unfortunately, the current state of research in offline MARL…