Homeostasis-inspired approaches can prevent catastrophic forgetting in deep reinforcement learning.

Catastrophic forgetting is when AI quickly loses old knowledge while learning new things. Homeostasis helps by keeping a balance between retaining old skills and learning new ones. This is done by regulating how much the AI updates its internal models, ensuring it doesn’t erase valuable information during learning.