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dc.contributor.authorRahmani, Vahid
dc.contributor.authorPelechano Gómez, Núria
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2021-12-02T10:02:06Z
dc.date.issued2022-02
dc.identifier.citationRahmani, V.; Pelechano, N. Towards a human-like approach to path finding. "Computers and graphics", Febrer 2022, vol. 102, p. 164-174.
dc.identifier.issn0097-8493
dc.identifier.urihttp://hdl.handle.net/2117/357635
dc.description.abstractPath finding for autonomous agents has been traditionally driven by finding optimal paths, typically by using A* search or any of its variants. When it comes to simulating virtual humanoids, traditional approaches rarely consider aspects of human memory or orientation. In this work, we propose a new path finding algorithm, inspired by current research regarding how the brain learns and builds cognitive maps. Our method represents the space as a hexagonal grid with counters, based on brain research that has investigated how memory cells are fired. Our path finder then combines a method for exploring unknown environments while building such a cognitive map, with an A* search using a modified heuristic that takes into account the cognitive map. The resulting paths show how as the agent learns the environment, the paths become shorter and more consistent with the optimal A* search. Moreover, we run a perceptual study to demonstrate that the viewers could successfully identify the intended level of knowledge of the simulated agents. This line of research could enhance the believability of autonomous agents’ path finding in video games and other VR applications.
dc.description.sponsorshipThis work was partly funded by the Spanish Ministry of Economy, Industry and Competitiveness under Grant No. TIN2017- 88515-C2-1-R.
dc.format.extent11 p.
dc.language.isoeng
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights©2021 Elsevier
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Infografia
dc.subject.lcshIntelligent agents (Computer software)
dc.subject.lcshVirtual reality
dc.subject.otherPathfinding
dc.subject.otherNeuroscience based simulation
dc.subject.otherAutonomous agents
dc.titleTowards a human-like approach to path finding
dc.typeArticle
dc.subject.lemacAgents intel·ligents (Programari)
dc.subject.lemacRealitat virtual
dc.contributor.groupUniversitat Politècnica de Catalunya. ViRVIG - Grup de Recerca en Visualització, Realitat Virtual i Interacció Gràfica
dc.identifier.doi10.1016/j.cag.2021.08.020
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/abs/pii/S0097849321001849
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac32106438
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-88515-C2-1-R/ES/VISUALIZACION, MODELADO, SIMULACION E INTERACCION CON MODELOS 3D. APLICACIONES EN CIENCIAS DE LA VIDA Y ENTORNOS RURALES Y URBANOS/
dc.date.lift2023-09-02
local.citation.authorRahmani, V.; Pelechano, N.
local.citation.publicationNameComputers and graphics
local.citation.volume102
local.citation.startingPage164
local.citation.endingPage174


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