Thesis (MSc)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: This study has started as part of a research project at Stellenbosch University
(SU) that aims at building a team of soccer-playing robots for the
RoboCup Small Size League (SSL). In the RoboCup SSL the Decision-
Making Module (DMM) plays an important role for it makes all decisions
for the robots in the team. This research focuses on the development of
some parts of the DMM for the team at SU.
A literature study showed that the DMM is typically developed in a
hierarchical structure where basic soccer skills form the fundamental building
blocks and high-level team behaviours are implemented using these basic
soccer skills. The literature study also revealed that strategies in the DMM
are usually developed using a hand-coded approach in the RoboCup SSL
domain, i.e., a specific and fixed strategy is coded, while in other leagues a
Machine Learning (ML) approach, Reinforcement Learning (RL) in particular,
is widely used. This led to the following research objective of this thesis,
namely to develop basic soccer skills using RL for the RoboCup Small Size
League. A second objective of this research is to develop a simulation environment
to facilitate the development of the DMM. A high-level simulator
was developed and validated as a result.
The temporal-difference value iteration algorithm with state-value functions
was used for RL, along with a Multi-Layer Perceptron (MLP) as a function
approximator. Two types of important soccer skills, namely shooting skills
and passing skills were developed using the RL and MLP combination. Nine
experiments were conducted to develop and evaluate these skills in various
playing situations. The results showed that the learning was very effective,
as the learning agent executed the shooting and passing tasks satisfactorily,
and further refinement is thus possible.
In conclusion, RL combined with MLP was successfully applied in this
research to develop two important basic soccer skills for robots in the
RoboCup SSL. These form a solid foundation for the development of a
complete DMM along with the simulation environment established in this
research. / AFRIKAANSE OPSOMMING: Hierdie studie het ontstaan as deel van 'n navorsingsprojek by Stellenbosch
Universiteit wat daarop gemik was om 'n span sokkerrobotte vir die
RoboCup Small Size League (SSL) te ontwikkel. Die besluitnemingsmodule
(BM) speel 'n belangrike rol in die RoboCup SSL, aangesien dit besluite vir
die robotte in die span maak. Hierdie navorsing fokus op ontwikkeling van
enkele komponente van die BM vir die span by SU.
'n Literatuurstudie het getoon dat die BM tipies ontwikkel word volgens
'n hiërargiese struktuur waarin basiese sokkervaardighede die fundamentele
boublokke vorm en hoëvlak spangedrag word dan gerealiseer deur hierdie
basiese vaardighede te gebruik. Die literatuur het ook getoon dat strategieë in die BM van die RoboCup SSL domein gewoonlik ontwikkel word deur
'n hand-gekodeerde benadering, dit wil s^e, 'n baie spesifieke en vaste strategie
word gekodeer, terwyl masjienleer (ML) en versterkingsleer (VL) wyd in
ander ligas gebruik word. Dit het gelei tot die navorsingsdoelwit in hierdie
tesis, naamlik om basiese sokkervaardighede vir robotte in die RoboCup SSL
te ontwikkel. 'n Tweede doelwit was om 'n simulasie-omgewing te ontwikkel
wat weer die ontwikkeling van die BM sou fasiliteer. Hierdie simulator is
suksesvol ontwikkel en gevalideer.
Die tydwaarde-verskil iterariewe algoritme met toestandwaarde-funksies is
gebruik vir VL saam met 'n multi-laag perseptron (MLP) vir funksiebenaderings.
Twee belangrike sokkervaardighede, naamlik doelskop- en aangeevaardighede
is met hierdie kombinasie van VL en MLP ontwikkel. Nege
eksperimente is uitgevoer om hierdie vaardighede in verskillende speelsituasies
te ontwikkel en te evalueer. Volgens die resultate was die leerproses baie
effektief, aangesien die leer-agent die doelskiet- en aangeetake bevredigend
uitgevoer het, en verdere verfyning is dus moontlik.
Die gevolgtrekking is dat VL gekombineer met MLP suksesvol toegepas is
in hierdie navorsingswerk om twee belangrike, basiese sokkervaardighede vir
robotte in die RoboCup SSL te ontwikkel. Dit vorm 'n sterk fondament vir
die ontwikkeling van 'n volledige BM tesame met die simulasie-omgewing
wat in hierdie werk daargestel is.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/96823 |
| Date | 03 1900 |
| Creators | Yoon, Moonyoung |
| Contributors | Bekker, James, Kroon, Steve, Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | 178 pages : illustrations |
| Rights | Stellenbosch University |
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