Combining Influence Maps and Potential Fields for AI Pathfinding

Combining Influence Maps and Potential Fields for AI Pathfinding

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-tim...

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Bibliographic Details
Main Authors: Pentikäinen, Filip, Sahlbom, Albin
Format: Others
Language:English
Published: Blekinge Tekniska Högskola, Institutionen för datavetenskap 2019
Subjects:
Pathfinding
Real-time performance
Influence map
Potential field
GPGPU
Realtidsprestanda
Computer Sciences
Datavetenskap (datalogi)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18228

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18228

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