Overview
Reinforcement Learning algorithms have been applied in different domains. Now there is a growing interest in applying RL algorithms to optimisation problems. Such algorithms are a better alternative to produce near-optimal solutions in dynamic environments, compared against exact or approximation algorithms. Benchmarks are a key element in the development and evaluation of novel algorithms as they enable a standardised comparison of these algorithms’ performance. In this project you will provide a set of optimisation benchmarks to evaluate online RL algorithms.
