Overview / Usage

Machine learning is a field of computer science that gives computers the ability to
learn without being explicitly programmed. Reinforcement learning (RL) is an
area of machine learning inspired by behaviourist psychology, concerned with how
software agents ought to take actions in an environment so as to maximize some
notion of cumulative reward.
Reinforcement Learning has been called as the first step towards general artificial
intelligence an AI that can survive in a variety of environments, instead of being
confined to strict realms such as playing chess. Artificial Intelligence is a way of
making a computer, a computer-controlled robot, or a software think intelligently,
in the similar manner the intelligent humans think. AI is accomplished by studying
how human brain thinks, and how humans learn, decide, and work while trying to
solve a problem, and then using the outcomes of this study as a basis of developing
intelligent software and systems.
The aim of this project is to combine Reinforcement Learning with other Machine
Learning techniques like Linear Function Approximation and Neural Networks to
train an agent to achieve high scores on popular Atari game Pacman.
I experiments with different algorithms, hyperparameters and network
architectures leading to better performance of my agent.