Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Meta-Reinforcement Learning via Evolution for Multi-Objective Combinatorial Supply Chain Optimisation
Rifny Rachman, Bahrul Ilmi Nasution, Josh Tingey +3
Meta-reinforcement learning is a promising approach to multi-objective optimisation because it enables rapid policy adaptation across changing environments and preference settings.…
cs.LG2025
Spatial-Aware Decision-Making with Ring Attractors in Reinforcement Learning Systems
Marcos Negre Saura, Richard Allmendinger, Wei Pan +1
Ring attractors, mathematical models inspired by neural circuit dynamics, provide a biologically plausible mechanism to improve learning speed and accuracy in Reinforcement Learnin…