Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Reinforcement learning AI to Hive
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Förstärkningslärande AI till Hive (Swedish)
Abstract [en]

This report is about the game Hive, which is a very unique board game. Firstly we cover what Hive is, and then later details on our implementations of it, which issues we ran into during the implementation and how we solved those issues. Also we attempted to make an AI and by using reinforcement learning teaching it to become good at playing Hive. More precisely we used two AI that has no knowledge of Hive other than game rules. This however turned out to be impossible within reasonable timeframe, our estimations is that it would have to run on an upper-end home computer for at least 140 years to become decent at playing the game.

Abstract [sv]

Denna rapport handlar om det unika brädspelet Hive. Rapporten kommer först berätta om vad Hive är och sedan gå in på detalj hur vi implementerar spelet, vad för problem vi stötte på och hur dessa problem löstes. Även så försökte vi göra en AI som lärde sig med hjälp av förstärkningslärning för att bli bra på spelet. Mer exakt så använde vi två AI som inte kunde något alls om Hive förutom spelreglerna. Detta visades vara omöjligt att genomföra inom rimlig tid, vår uppskattning är att det skulle ha tagit en bra stationär hemdator minst 140 år att lära en AI spel Hive på en godtagbar nivå.

Place, publisher, year, edition, pages
2013.
Series
Kandidatexjobb CSC, K13019
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-134908OAI: oai:DiVA.org:kth-134908DiVA: diva2:668701
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2013-12-13 Created: 2013-12-02 Last updated: 2013-12-13Bibliographically approved

Open Access in DiVA

Reinforcement learning AI to Hive(391 kB)142 downloads
File information
File name FULLTEXT01.pdfFile size 391 kBChecksum SHA-512
ccb08d1e26d42fd5269e9f9dd51a3f4880842dbd9fec2b18a20eb36b2ffeb38858e4b8d009379dd4852fe4583a1339bb196b898fa56e63eaa8f5d934897a88de
Type fulltextMimetype application/pdf

Other links

http://www.csc.kth.se/utbildning/kth/kurser/DD143X/dkand13/Group4Per/report/8-blixt-ye.pdf
By organisation
School of Computer Science and Communication (CSC)
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 142 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 348 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf