Advances in deep reinforcement learning have allowed autonomous agents to perform well
on Atari games, often outperforming humans, using only raw pixels to make their decisions …

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 …

This research focuses on developing AI agents that play arbitrary Atari 2600 console games
without having any game-specific assumptions or prior knowledge. Two main approaches …

Q-learning is a popular reinforcement learning technique for solving shortest path (STP)
problem. In a maze with multiple sub-tasks such as collecting treasures and avoiding traps, it …

The aim of intelligent techniques, termed game AI, used in computer video games is to
provide an interesting and challenging game play to a game player. Being highly …

In the context of the actor–partner interdependence model, this study examined the
influence of friendship quality on console-gaming aggression (ie, verbal aggression …

Reinforcement learning is well suited to first person shooter bot artificial intelligence as it has
the potential to create diverse behaviors without the need to implicitly code them. This paper …

An effective way to achieve intelligence is to simulate various intelligent behaviors in the
human brain. In recent years, bio-inspired learning methods have emerged, and they are …

A first person shooter game is a game genre where fun in the game resorts to the skill of the
opponents. In particular, when the opponents are bots, adjustment of their skill levels as well …

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 …