Will more realistic behaviour among non-playing characters (NPCs) in a role-playing game(RPG) improve the overall feeling of the game for the player? Would players notice the enhanced life of a NPC in a role-playing game, or is the time spent in cities and villages insufficient to notice any difference at all? There are plenty best-selling RPGs with simplistic, repetitive NPC behaviour on the market. Does that mean that smarter NPCs is not necessary and that an improvement of them wouldn't benefit the players' impression of it? Or would some of these well recognised games get even better with a more evolved AI? These are some of the thoughts that created the initial spark of curiosity that inspired the making of this article. By assuming that a more complex game AI for the NPCs will improve the realism and feeling in a role-playing game, a research about possible techniques to achieve this was made. The technique Smart Terrain was found most beneficial for the purpose with this research. It's been used successfully in the well-selling game The Sims and appeared to be a good choice for an NPC AI with the flexibility and expandability it delivers. With a technique of great potential selected, a first version of an AI using it was implemented as a module to the commercial RPG Neverwinter Nights 2(NWN2). With the implemented Smart Terrain AI at hand, twelve testers got to compare this AI with the one that is encountered in the original campaign of NWN2. As all the participants in the test thought the new version of the AI more realistic than the original AI, the hypothesis was proven to be true. The results gave a strong indication of that using the Smart Terrain technique is a good choice to achieve higher realism among non-hostile NPCs in a RPG like NWN2.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-5016 |
Date | January 2008 |
Creators | Jeppsson, Bertil |
Publisher | Blekinge Tekniska Högskola, Avdelningen för programvarusystem |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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