3 papers
cs.LG2026
Self-Supervised On-Policy Reinforcement Learning via Contrastive Proximal Policy Optimisation
Asim Osman, Sasha Abramowitz, Mark Bergh +13
Contrastive reinforcement learning (CRL) learns goal-conditioned Q-values through a contrastive objective over state-action and goal representations, removing the need for hand-cra…
cs.LG2025
Breaking the Performance Ceiling in Reinforcement Learning requires Inference Strategies
Felix Chalumeau, Daniel Rajaonarivonivelomanantsoa, Ruan de Kock +12
Reinforcement learning (RL) systems have countless applications, from energy-grid management to protein design. However, such real-world scenarios are often extremely difficult, co…
cs.AI2025
Memory-Enhanced Neural Solvers for Routing Problems
Felix Chalumeau, Refiloe Shabe, Noah De Nicola +3
Routing Problems are central to many real-world applications, yet remain challenging due to their (NP-)hard nature. Amongst existing approaches, heuristics often offer the best tra…