Reinforcement learning (RL) is a popular machine learning technique that has many
successes in learning how to play classic style games. Applying RL to first person shooter …

We describe the architecture of a hierarchical learning-based controller for bots in the First-
Person Shooter (FPS) game Unreal Tournament 2004. The controller is inspired by the …

This paper is an initial approach to create a controller for the game TORCS by learning how
another controller or humans play the game. We used data obtained from two controllers …

Artificial Intelligence in the form of machine learning is employed in games to control non-
human computer-players, agents or bots. However, most of these games such as Atari took …

In this paper we employ a steady state genetic algorithm to evolve different types of
behaviour for bots in the Unreal Tournament 2004™ computer game. For this purpose we …

In this article we introduce Rogueinabox: a highly modular learning environment built
around the videogame Rogue, the father of the roguelike genre. It offers easy ways to …

In the game industry, developers and their audience often refer to decisionmaking systems
like behaviour trees, finite state machine or utility theory when referring to Game AI. These …

Non-player characters which benefit from artificial intelligence play a significant role in video
games. Due to the vast state spaces of some video games these agents must have access to …

The game is a field of science is growing rapidly and very interesting to learn because
review has potential good view of science and commercial aspect. To produce an attractive …

Autonomous agents in videogames, usually called bots, have tried to behave as human
players from their emergence more than 20 years ago. They normally try to model a part of a …