This paper presents a comprehensive review of deep learning applications in the video
game industry, focusing on how these techniques can be utilized in game development …

Iterative user-centred design has become a standard approach for develo** interactive
products. This process relies on prototy** and usertesting as early as possible to deliver a …

Autonomous driving has emerged as one of the most active areas of research as it has the
promise of making transportation safer and more efficient than ever before. Most real-world …

Abstract Develo** Non-Player Characters, ie, game characters that interact with the
game's environment autonomously with flexibility to experiment different behavior …

Deep reinforcement learning (Deep RL) algorithms are defined with fully continuous or
discrete action spaces. Among DRL algorithms, soft actor–critic (SAC) is a powerful method …

Deep Reinforcement Learning (RL) algorithms are widely being used in autonomous driving
due to their ability to cope with unseen environments. However, in a complex domain like …

Game agents which are behavioral agent for game playing are a crucial component of game
satisfaction. However it takes a lot of time and effort to create game agents for various game …

In the article a method which is able to provide the required performance level of a system is
proposed. Its principle is to combine the results of conventional control methods with those …

Reinforcement learning methods achieve performance superior to humans in a wide range
of complex tasks and uncertain environments. However, high performance is not the sole …

We introduce a new reward function direction for intrinsically motivated reinforcement
learning to mimic human behavior in the context of computer games. Similar to previous …