Summary
In this chapter you re-applied deep Q-learning to a new business problem. You were supposed to find the best strategy to cool down and heat up the server. Before you started defining the AI strategy, you had to make some assumptions about your environment, for example the way the temperature is calculated. As inputs to your ANN, you had information about the server at any given time, like the temperature and data transmission. As outputs, your AI predicted whether to cool down or heat up our server by a certain amount. The reward was the energy saved with respect to the other, traditional cooling system. Your AI was able to save 87% energy.