Reinforcement Learning Algorithms with Python

Unboxing algorithm selection

To better understand what ESBAS does, let's first focus on what algorithm selection (AS) is. In normal settings, a specific and fixed algorithm is developed and trained for a given task. The problem is that if the dataset changes over time, the dataset overfits, or another algorithm works better in some restricted contexts, there's no way of changing it. The chosen algorithm will remain the same forever. The task of algorithm selection overcomes this problem.

AS is an open problem in machine learning. It is about designing an algorithm called a meta-algorithm that always chooses the best algorithm from a pool of different options, called a portfolio, which is based on current needs. A representation of this is ...