Efficient Open-world Reinforcement Learning via Knowledge Distillation and Autonomous Rule Discovery

Ekaterina Nikonova, Cheng Xue, Jochen Renz

Deep reinforcement learning suffers from catastrophic forgetting and sample inefficiency making it less applicable to the ever-changing real world. However, the ability to use prev…