The Reptile algorithm has been proposed as an improvement to MAML by OpenAI. It's simple and easier to implement. We know that, in MAML, we calculate second order derivatives—that is, the gradient of gradients. But computationally, this isn't an efficient task. So, OpenAI came up with an improvement over MAML called Reptile. The algorithm of Reptile is very simple. Sample some n number of tasks and run Stochastic Gradient Descent (SGD) for fewer iterations on each of the sampled tasks and then update our model parameter in a direction that's common to all of the tasks. Since we're performing SGD for fewer iterations on each task, it indirectly implies we're calculating the second order derivative over the loss. Unlike MAML, it's computationally effective as we're not calculating the second order derivative directly nor unrolling the computational graph, and so it is easier to implement.
Let's say we sampled two tasks,
, from the task distribution and we randomly initialize the...