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Performance Comparison of AI Algorithms: Anytime Algorithms
Blekinge Institute of Technology, School of Engineering, Department of Systems and Software Engineering.
2008 (English)Independent thesis Advanced level (degree of Master (One Year))Student thesisAlternative title
Utförande Jämförelse av AI Algoritmer : Anytime Algoritmer (Swedish)
Abstract [en]

Commercial computer gaming is a large growing industry that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards due to some fundamental AI problems those require more research to be better solved for the RTS games. There also exist some AI algorithms those can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for an AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of our selected anytime algorithms for an AI problem.

Place, publisher, year, edition, pages
2008. , 75 p.
Keyword [en]
Artificial Intelligence (AI), Real Time Strategy (RTS) Games, AI Algorithms, AI Problems, Anytime Algorithms, A – Star, RBFS, Potential Fields, Path Finding, ORTS platform, PFPC platform
National Category
Computer Science Human Computer Interaction
URN: urn:nbn:se:bth-5845Local ID: diva2:833251
Address: NaN Mob. +46 - 737 - 40 19 17Available from: 2015-04-22 Created: 2008-12-04 Last updated: 2015-06-30Bibliographically approved

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