Design and Implementation of ImALeG Serious Game: Behavior of Non-playable Characters (NPC)

Tazouti, Yassine; Boulaknadel, Siham; Fakhri, Yadolah

doi:10.1007/978-981-16-5559-3_7

Cited by 3 publications

(1 citation statement)

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“…Many games have multiple non-player characters (NPCs) who play with the player, against them or take a neutral position within the game. They play an essential part in video games to increase the player experience and should therefore be supplied with a fitting behavior by creating a fitting Artificial Intelligence (AI) for them [2].…”

Section: Introductionmentioning

confidence: 99%

Reinforcement Learning Toolkits for Gaming: A Comparative Qualitative Analysis

Mekni¹,

Jayaramireddy²,

Naraharisetti³

2022

JSEA

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Historically viewed as a niche economic sector, gaming is now projected to exceed a global annual revenue of $218.7 billion in 2024, taking advantage of recent Artificial Intelligence (AI) advances. In recent years, specific AI techniques namely; Machine Learning (ML) and Reinforcement Learning (RL), have seen impressive progress and popularity. Techniques developed within these two fields are now able to analyze and learn from gameplay experiences enabling more interactive, immersive, and engaging games. While the number of ML and RL algorithms is growing, their implementations through frameworks and toolkits are also extensive too. Moreover, the game design and development community lacks a framework for informed evaluation of available RL toolkits. In this paper, we present a comprehensive survey of RL toolkits for games using a qualitative evaluation methodology.

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Section: Introductionmentioning

confidence: 99%