BIMRL: Brain Inspired Meta Reinforcement Learning
Seyed Roozbeh Razavi Rohani,Saeed Hedayatian,Mahdieh Soleymani Baghshah,Seyed Roozbeh Razavi Rohani,Saeed Hedayatian,Mahdieh Soleymani Baghshah
Sample efficiency has been a key issue in reinforcement learning (RL). An efficient agent must be able to leverage its prior experiences to quickly adapt to similar, but new tasks and situations. Meta-RL is one attempt at formalizing and ad-dressing this issue. Inspired by recent progress in meta-RL, we introduce BIMRL, a novel multi-layer architecture along with a novel brain-inspired memory modu...
