Release:№8 2019. 05.00.00 ТЕХНИЧЕСКИЕ НАУКИ
About the authors:Sizova Lyudmila Vladimirovna, Senior lecturer, University of Tyumen,
Bachelor student, University of Tyumen,Bachelor student, University of Tyumen, firstname.lastname@example.org
More than ten years after the first research in the use of artificial intelligence (AI) in computer games and the creation of the new field called AI, the term “gaming AI” needs to be redefined. Traditionally, tasks related to game AI revolved around the behavior of a non-player character (NPC) at different levels of control, from navigation and path finding to decision-making. Commercial standard games developed over the past 15 years and current gaming developments suggest that the traditional problems of gaming AI have been well resolved using sophisticated AI approaches that are not necessarily followed or inspired by academic advances. The existence of the gap between industry and academics is due to the fact that the academic approach to AI development is not able to offer industry methods that can significantly improve the existing design process or provide scalable solutions to real problems. Recently, however, a shift in research has appeared. Some of these alternative uses for AI have already shown significant potential for use in commercial projects. This article presents three key areas of research for gaming AI that are currently reshaping the game AI field.
1. Houlette R. (2003) Player Modeling for Adaptive Games. AI Game Programming Wisdom II. Ed. 2. Eds. Charles River Media, p. 732.
2. Yannakakis G.N., Togelius J. (2007) Experience-Driven Procedural Content Generation. IEEE Transactions on Affective Computing. p. 16.
3. Drachen A., Calleja G. (2011) In-Game: From Immersion to Incorporation. The MIT Press. p. 240.
4. Yannakakis G.N., Hallam J. (2007) Towards Optimizing Entertainment in Computer Games. Applied Artificial Intelligence, 21 (10). p. 39.
5. Champandard A.J. (2003) AI Game Development. New Riders Publishing. p. 762.