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Randomized tree construction algorithm to explore energy landscapes
Jaillet, Leonard Georges; Corcho Sánchez, Francisco José; Pérez González, Juan Jesús; Cortés, Juan
Universitat Politècnica de Catalunya. Departament d'Enginyeria Química; Universitat Politècnica de Catalunya. Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI; Universitat Politècnica de Catalunya. ENGMOL - Enginyeria Molecular
We 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.
Control predictiu
Predictive control
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial artificial
Classificació INSPEC::Cybernetics::Artificial intelligence::Planning (artificial intelligence)::Path planning
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/submittedVersion
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