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DC Field | Value | Language |
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dc.contributor.author | Yannakakis, Georgios N. | - |
dc.date.accessioned | 2018-04-26T09:11:17Z | - |
dc.date.available | 2018-04-26T09:11:17Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Yannakakis, G. N. (2012). Game AI revisited. 9th Conference on Computing Frontiers, Caligari. 285-292. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/29591 | - |
dc.description.abstract | More than a decade after the early research efforts on the use of artificial intelligence (AI) in computer games and the establishment of a new AI domain the term “game AI” needs to be redefined. Traditionally, the tasks associated with game AI revolved around non player character (NPC) behavior at different levels of control, varying from navigation and pathfinding to decision making. Commercial-standard games developed over the last 15 years and current game productions, however, suggest that the traditional challenges of game AI have been well addressed via the use of sophisticated AI approaches, not necessarily following or inspired by advances in academic practices. The marginal penetration of traditional academic game AI methods in industrial productions has been mainly due to the lack of constructive communication between academia and industry in the early days of academic game AI, and the inability of academic game AI to propose methods that would significantly advance existing development processes or provide scalable solutions to real world problems. Recently, however, there has been a shift of research focus as the current plethora of AI uses in games is breaking the non-player character AI tradition. A number of those alternative AI uses have already shown a significant potential for the design of better games. This paper presents four key game AI research areas that are currently reshaping the research roadmap in the game AI field and evidently put the game AI term under a new perspective. These game AI flagship research areas include the computational modeling of player experience, the procedural generation of content, the mining of player data on massive-scale and the alternative AI research foci for enhancing NPC capabilities. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | ACM | en_GB |
dc.rights | info:eu-repo/semantics/openAccess | en_GB |
dc.subject | Artificial intelligence | en_GB |
dc.subject | Video games | en_GB |
dc.subject | Computer games -- Design | en_GB |
dc.subject | Human-computer interaction | en_GB |
dc.subject | Human-machine systems | en_GB |
dc.title | Game AI revisited | en_GB |
dc.type | conferenceObject | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder | en_GB |
dc.bibliographicCitation.conferencename | 9th Conference on Computing Frontiers | en_GB |
dc.bibliographicCitation.conferenceplace | Caligari, Italy, 15-17/05/2012 | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
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Game_AI_revisited.pdf | 469.93 kB | Adobe PDF | View/Open |
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