Hands-On Meta Learning with Python

MAML in reinforcement learning

How can we apply MAML in a reinforcement learning (RL) setting? In RL, our objective is to find the right policy function that will tell us what actions to perform in each state. But how can we apply meta learning in RL? Let's say we trained our agent to solve the two-armed bandit problem. However, we can't use the same agent to solve the four-armed bandit problem. We have to train the agent again from scratch to solve this new four-armed bandit problem. This is the same case when another n-armed bandit comes in. We keep training our agent from scratch to solve new problems even though it is closely related to the problem that the agent has already learned to solve. So, instead of doing this, we can apply meta ...