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
Combining Influence Maps and Potential Fields for AI Pathfinding
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This thesis explores the combination of influence maps and potential fields in two novel pathfinding algorithms, IM+PF and IM/PF, that allows AI agents to intelligently navigate an environment. The novel algorithms are compared to two established pathfinding algorithms, A* and A*+PF, in the real-time strategy (RTS) game StarCraft 2.

The main focus of the thesis is to evaluate the pathfinding capabilities and real-time performance of the novel algorithms in comparison to the established pathfinding algorithms. Based on the results of the evaluation, general use cases of the novel algorithms are presented, as well as an assessment if the novel algorithms can be used in modern games.

The novel algorithms’ pathfinding capabilities, as well as performance scalability, are compared to established pathfinding algorithms to evaluate the viability of the novel solutions. Several experiments are created, using StarCraft 2’s base game as a benchmarking tool, where various aspects of the algorithms are tested. The creation of influence maps and potential fields in real-time are highly parallelizable, and are therefore done in a GPGPU solution, to accurately assess all algorithms’ real-time performance in a game environment.

The experiments yield mixed results, showing better pathfinding and scalability performance by the novel algorithms in certain situations. Since the algorithms utilizing potential fields enable agents to inherently avoid and engage units in the environment, they have an advantage in experiments where such qualities are assessed. Similarly, influence maps enable agents to traverse the map more efficiently than simple A*, giving agents inherent advantages.

In certain use cases, where multiple agents require pathfinding to the same destination, creating a single influence map is more beneficial than generating separate A* paths for each agent. The main benefits of generating the influence map, compared to A*-based solutions, being the lower total compute time, more precise pathfinding and the possibility of pre-calculating the map.

Abstract [sv]

Denna rapport utforskar kombinationen av influence maps och potential fields med två nya pathfinding algoritmer, IM+PF och IM/PF, som möjliggör intelligent navigation av AI agenter. De nya algoritmerna jämförs med två existerande pathfindingalgoritmer, A* och A*+PF, i realtidsstrategispelet StarCraft 2.

Rapportens fokus är att utvärdera de nya algoritmernas pathfindingförmåga samt realtidsprestanda i förhållande till de två existerande algoritmerna, i sex olika experiment. Baserat på resultaten av experimenten presenteras generella användningsområden för algoritmerna tillsammans med en bedömning om algoritmerna kan användas i moderna spel.

De fyra pathfindingalgoritmerna implementeras för att jämföra pathfindingförmåga och realtidsprestanda, för att dra slutsatser angående de nya algoritmernas livsduglighet. Med användningen av StarCraft 2 som ett benchmarkingvertyg skapas sex experiment där olika aspekter av algoritmerna testas. Genereringen av influence maps och potential fields i realtid är ett arbete som kan parallelliseras, och därför implementeras en GPGPU-lösning för att få en meningsfull representation av realtidsprestandan av algoritmerna i en spelmiljö.

Experimenten visar att de nya algoritmerna presterar bättre i både pathfindingförmåga och skalbarhet under vissa förhållanden. Algoritmerna som använder potential fields har en stor fördel gentemot simpel A*, då agenterna kan naturligt undvika eller konfrontera enheter i miljön, vilket ger de algoritmerna stora fördelar i experiment där sådana förmågor utvärderas. Influence maps ger likväl egna fördelar gentemot A*, då agenter som utnyttjar influence maps kan traversera världen mer effektivt.

Under förhållanden då flera AI agenter ska traversera en värld till samma mål kan det vara förmånligt att skapa en influence map, jämfört med att generera individuella A*-vägar till varje agent. De huvudsakliga fördelarna för de influence map-baserade algoritmerna är att de kräver lägre total beräkningstid och ger en merexakt pathfinding, samt möjligheten att förberäkna influence map-texturen.

Place, publisher, year, edition, pages
2019. , p. 52
Keywords [en]
Pathfinding, Real-time performance, Influence map, Potential field, GPGPU
Keywords [sv]
Pathfinding, Realtidsprestanda, Influence map, Potential field, GPGPU
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-18228OAI: oai:DiVA.org:bth-18228DiVA, id: diva2:1332110
Subject / course
Degree Project in Master of Science in Engineering 30,0 hp
Educational program
PAACI Master of Science in Game and Software Engineering
Presentation
(English)
Supervisors
Examiners
Available from: 2019-07-08 Created: 2019-06-27 Last updated: 2019-07-08Bibliographically approved

Open Access in DiVA

fulltext(2975 kB)20 downloads
File information
File name FULLTEXT01.pdfFile size 2975 kBChecksum SHA-512
e18e7c1ef022e20ea51d7f5bbce427c2b628addc851a6e4b3a01ba4b9f8b314bd60c601bb544d811858af24c303bcf292348ceb91e933ad90c6d41adc114114c
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Pentikäinen, FilipSahlbom, Albin
By organisation
Department of Computer Science
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 20 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: 52 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