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dc.contributor.authorJaillet, Leonard Georges
dc.contributor.authorCorcho Sánchez, Francisco José
dc.contributor.authorPérez González, Juan Jesús
dc.contributor.authorCortés, Juan
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Química
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2012-01-10T18:27:45Z
dc.date.available2012-01-10T18:27:45Z
dc.date.created2011-12
dc.date.issued2011-12
dc.identifier.citationJaillet, L. [et al.]. Randomized tree construction algorithm to explore energy landscapes. "Journal of computational chemistry", Desembre 2011, vol. 32, núm. 16, p. 3464-3474.
dc.identifier.issn0192-8651
dc.identifier.urihttp://hdl.handle.net/2117/14456
dc.description.abstractWe report in the present work a new method for exploring conformational energy landscapes. The method, called T-RRT, combines ideas from statistical physics and robot path planning algorithms. A search tree is constructed on the conformational space starting from a given state. The tree expansion is driven by a double strategy: on the one hand, it is naturally biased towards yet unexplored regions of the space; on the other, a Monte Carlo-like transition test guides the expansion toward energetically favorable regions. The balance between these two strategies is automatically achieved thanks to a self-tuning mechanism. The method is able to efficiently find both, energy minima and transition paths between them. As a proof of concept, the method is applied to two academic benchmarks and to the alanine dipeptide.
dc.format.extent11 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.classificationControl predictiu
dc.subject.lcshPredictive control
dc.titleRandomized tree construction algorithm to explore energy landscapes
dc.typeArticle
dc.subject.lemacÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial artificial
dc.contributor.groupUniversitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
dc.contributor.groupUniversitat Politècnica de Catalunya. ENGMOL - Enginyeria Molecular
dc.identifier.doi10.1002/jcc.21931
dc.subject.inspecClassificació INSPEC::Cybernetics::Artificial intelligence::Planning (artificial intelligence)::Path planning
dc.rights.accessOpen Access
local.identifier.drac8599840
dc.description.versionPostprint (author’s final draft)
local.citation.authorJaillet, L.; Corcho, F.; Pérez, J.; Cortés, J.
local.citation.publicationNameJournal of computational chemistry
local.citation.volume32
local.citation.number16
local.citation.startingPage3464
local.citation.endingPage3474


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Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain