Project Title
Enhancing Game Intelligence: A Study on Artificial in Game Development
Introduction and Origin of the Research Problems
The integration of artificial intelligence (AI) in gaming has evolved significantly over the past few
decades. Historically, game AI was primarily focused on simple algorithms for NPC behavior.
However, with advancements in machine learning, neural networks, and computational theories,
the potential for creating more immersive, adaptive, and intelligent game experiences has
surged. This research aims to explore how these technologies can enhance player engagement
and game complexity, addressing the gap in understanding the full spectrum of AI in modern
game design.
Social Relevance
The gaming industry is a multi-billion-dollar sector that influences entertainment, education, and
social interaction. As games increasingly become platforms for storytelling and social
engagement, the implementation of advanced AI can lead to more personalized and enriching
experiences. Understanding and improving AI in games can also influence the development of
AI in other sectors, such as simulation training, educational tools, and virtual reality experiences,
making this research socially significant.
Introduction of Research and Development in the Subject
Recent advancements in AI have opened new frontiers for game development. Techniques such
as procedural generation, reinforcement learning, and deep learning are being employed to
create dynamic environments and intelligent behaviors. This research will analyze existing
methodologies and propose innovative approaches to enhance AI capabilities in games,
focusing on player experience and game design efficiency.
National/International Status
Globally, countries like the USA, Japan, and Canada are at the forefront of integrating AI into
gaming. Leading companies such as Google DeepMind, Ubisoft, and Electronic Arts are
investing heavily in R&D to leverage AI technologies. Nationally, there is a growing emphasis on
fostering innovation in gaming technology, with academic institutions and startups collaborating
to advance research in this field.
Objective
The primary objectives of this research are:
1. To investigate the current state of AI in games and identify gaps in knowledge.
2. To develop new AI frameworks that enhance gameplay and player interaction.
3. To assess the impact of advanced AI on player engagement and satisfaction.
Methodology
The research will employ a mixed-methods approach:
● Literature Review: Analyzing existing studies on AI in gaming.
● Case Studies: Evaluating successful implementations of AI in various game genres.
● Prototyping: Developing a prototype game that utilizes advanced AI techniques to
demonstrate findings.
● Surveys and User Testing: Gathering player feedback to assess the effectiveness of AI
enhancements on gameplay experience.
Results and Outcome
The expected outcomes of this research include:
● A comprehensive understanding of current AI applications in gaming. ●
Development of a prototype demonstrating innovative AI techniques. ●
Recommendations for game developers on implementing AI to enhance player
engagement.
● Contributions to academic literature and potential frameworks for future research in
game AI.
Bibliography
1. Yannakakis, Georgios N., and Julian Togelius. "A panorama of artificial and
computational intelligence in games." IEEE Transactions on Computational Intelligence
and AI in Games 7.4 (2014): 317-335.
2. Yannakakis, Georgios N., and Julian Togelius. Artificial intelligence and games. Vol. 2.
New York: Springer, 2018.
3. Borovikov, Igor, et al. "Towards interactive training of non-player characters in video
games." arXiv preprint arXiv:1906.00535 (2019).
4. Zhao, Yunqi, et al. "Winning is not everything: Enhancing game development with
intelligent agents." IEEE Transactions on Games 12.2 (2020): 199-212.
5. Ojha, Suman, et al. "Integrating personality and mood with agent emotions." 18th
International Conference on Autonomous Agents and MultiAgent Systems (AAMAS).
ASSOC COMPUTING MACHINERY, 2019.
