3 papers
cs.AI2026
Characterizing MARL for Energy Control: A Multi-KPI Benchmark on the CityLearn Environment
Aymen Khouja, Imen Jendoubi, Oumayma Mahjoub +4
The optimization of urban energy systems is crucial for the advancement of sustainable and resilient smart cities, which are becoming increasingly complex with multiple decision-ma…
cs.LG2025
Oryx: a Scalable Sequence Model for Many-Agent Coordination in Offline MARL
Claude Formanek, Omayma Mahjoub, Louay Ben Nessir +10
A key challenge in offline multi-agent reinforcement learning (MARL) is achieving effective many-agent multi-step coordination in complex environments. In this work, we propose Ory…
cs.LG2023
Generalisable Agents for Neural Network Optimisation
Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz +5
Optimising deep neural networks is a challenging task due to complex training dynamics, high computational requirements, and long training times. To address this difficulty, we pro…