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DC Field | Value | Language |
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dc.date.accessioned | 2021-04-26T13:34:55Z | - |
dc.date.available | 2021-04-26T13:34:55Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Kudde, D. (2019). Conflict of nations (Bachelor's dissertation). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/74758 | - |
dc.description | B.SC.ICT(HONS)ARTIFICIAL INTELLIGENCE | en_GB |
dc.description.abstract | One of the most prevailing problems the gaming industry faces today is designing A.I systems that produce non-player characters (NPCs) which are capable of exhibiting intelligent and adaptive behaviour in ever more complex environments. This is especially true when it comes to real-time strategy games (RTS) were the game environment tend to be more complex and generally boast a larger action-state space than most other game genres. Whilst such environments make for a complex, well detailed games with in-depth gameplay such as StarCraft, Age Of Empires and Tropico, they also impose great restrictions when it comes to designing A.I systems within them. It is important to note that the primary goal of any game is first and foremost to provide entertainment to the end user as such any A.I system must not only be capable of adapting to ever changing circumstances but also sufficiently provide enough of a challenge to the players to keep them alerted and engaged while not challenging enough to completely overwhelm them. To this end we introduce CONAI, an artifi cial system set in the online RTS game called Conflict Of Nations. CONAI is an AI system working within a goal-driven autonomy (GDA) framework which uses reinforcement learning to learn the most appropriate strategies at any given situation. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Computer games | en_GB |
dc.subject | Artificial intelligence | en_GB |
dc.subject | Machine learning | en_GB |
dc.title | Conflict of nations | en_GB |
dc.type | bachelorThesis | 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.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Information and Communication Technology. Department of Artificial Intelligence | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Kudde, Dale (2019) | - |
Appears in Collections: | Dissertations - FacICT - 2019 Dissertations - FacICTAI - 2019 |
Files in This Item:
File | Description | Size | Format | |
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Kudde Dale.pdf Restricted Access | 1.4 MB | Adobe PDF | View/Open Request a copy |
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