Implementing Reinforcement Learning to Design a Game Bot

Abstract

Artificial intelligence is the technology of the future, it has accomplished tasks that were assumed to be impossible earlier. It has very promising future aspects. It has proven to be useful in almost every field. Training an artificial intelligence model requires a lot of data. 90% of world’s total data has been generated over last two years only. Sometimes it is not feasible to have such huge amounts of data to train models. Here, comes in the situation “reinforcement learning” where the agent learns from the environment. Reinforcement learning has been applied to various fields like manufacturing, inventory management, delivery management, power systems, finance sectors and self-driving cars. Using the same procedure an artificial agent can be trained to perform desirable tasks. In this paper we discuss the implementation of reinforcement learning to develop a bot that plays a game just like humans.