Some of the most important RL algorithms for business applications are: 1. deep Q-learning (DQN): DQN is a powerful algorithm that can be used to solve a variety of problems. It is particularly well suited for problems where the environment is partially observable. 2. trust region policy optimisation (TRPO): TRPO is a robust algorithm that can be used to solve problems with high-dimensional state and action spaces. 3. proximal policy optimisation (PPO): PPO is a newer algorithm that is often considered the most modern algorithm for RL. It is particularly well suited for problems with continuous action spaces. 4. Asynchronous Advantage Actor-Critic (A3C): A3C provides stability and generalisation across different tasks and environments through an actor-critical architecture. It offers parallelisation for faster convergence and better exploration in reinforcement learning.