Inlämning av Examensarbete / Submission of Thesis

Rehman Butt MCS-2008:35, pp. 75. TEK/avd. för programvaruteknik, 2008.

The work

Författare / Author: Rehman Butt
Titel / Title: Performance Comparison of AI Algorithms - Anytime Algorithms
Översatt titel / Translated title: Utförande Jämförelse av AI Algoritmer - Anytime Algoritmer
Abstrakt Abstract:

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 because of some broad sets of problems. Some of these problems have been solved with the advent of an open real time research platform, named as ORTS. However there still exist some fundamental AI problems that require more research to be better solved for the RTS games. There also exist some AI algorithms that 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 for the RTS games. 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 each AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of selected anytime algorithms for an AI problem

Ämnesord / Subject: Datavetenskap - Computer Science\Artificial Intelligence
Spelutveckling - Digital Game Development
Nyckelord / Keywords: 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

Publication info

Dokument id / Document id:
Program:/ Programme Magisterprogram i Datavetenskap/MSC in Computer science
Registreringsdatum / Date of registration: 12/08/2008
Uppsatstyp / Type of thesis: Magisterarbete/Master's Thesis (60 credits)


Handledare / Supervisor: Stefan Johansson
Examinator / Examiner: Guohua Bai
Organisation / Organisation: Blekinge Institute of Technology
Institution / School: TEK/avd. för programvaruteknik
S-372 25 Ronneby
+46 455 38 50 00

Files & Access

Bifogad uppsats fil(er) / Files attached: thesis_report_rehman.pdf (729 kB, öppnas i nytt fönster)