How much can change in a year? Revisiting Evaluation in Multi-Agent Reinforcement Learning. - Siddarth Singh; Omayma Mahjoub; Ruan de Kock; Wiem Khlifi; Abidine Vall; Kale-ab Abebe Tessera; Arnu Pretorius (CoRR, 2023)

Efficiently Quantifying Individual Agent Importance in Cooperative MARL. - Omayma Mahjoub; Ruan de Kock; Siddarth Singh; Wiem Khlifi; Abidine Vall; Kale-ab Abebe Tessera; Arnu Pretorius (CoRR, 2023)

On Diagnostics for Understanding Agent Training Behaviour in Cooperative MARL. - Wiem Khlifi; Siddarth Singh; Omayma Mahjoub; Ruan de Kock; Abidine Vall; Rihab Gorsane; Arnu Pretorius (CoRR, 2023)

Performant, Memory Efficient and Scalable Multi-Agent Reinforcement Learning. - Omayma Mahjoub; Sasha Abramowitz; Ruan de Kock; Wiem Khlifi; Simon du Toit; Jemma Daniel; Louay Ben Nessir; Louise Beyers; Claude Formanek; Liam Clark; Arnu Pretorius (CoRR, 2024)

Multi-Agent Reinforcement Learning with Selective State-Space Models. - Jemma Daniel; Ruan John de Kock; Louay Ben Nessir; Sasha Abramowitz; Omayma Mahjoub; Wiem Khlifi; Juan Claude Formanek; Arnu Pretorius (AAMAS, 2025)

Breaking the Performance Ceiling in Complex Reinforcement Learning requires Inference Strategies. - Félix Chalumeau; Daniel Rajaonarivonivelomanantsoa; Ruan de Kock; Claude Formanek; Sasha Abramowitz; Omayma Mahjoub; Wiem Khlifi; Simon du Toit; Louay Ben Nessir; Refiloe Shabe; Arnol Fokam; Siddarth Singh; et al. (CoRR, 2025)

Oryx: a Performant and Scalable Algorithm for Many-Agent Coordination in Offline MARL. - Claude Formanek; Omayma Mahjoub; Louay Ben Nessir; Sasha Abramowitz; Ruan de Kock; Wiem Khlifi; Simon du Toit; Félix Chalumeau; Daniel Rajaonarivonivelomanantsoa; Arnol Fokam; Siddarth Singh; Ulrich A. Mbou Sob; et al. (CoRR, 2025)