Zobrazeno 1 - 10
of 611
pro vyhledávání: '"Tomas Lozano"'
\textit{Graph neural networks} (GNNs) are effective models for many dynamical systems consisting of entities and relations. Although most GNN applications assume a single type of entity and relation, many situations involve multiple types of interact
Externí odkaz:
http://arxiv.org/abs/2310.07015
Autor:
Mann, Kristin Dutcher
Publikováno v:
The Southwestern Historical Quarterly, 2008 Apr 01. 111(4), 443-444.
Externí odkaz:
https://www.jstor.org/stable/30242404
Autor:
Cristina S. Torres-Castillo, José E. Fuentes-Agustín, Eric M. García-Reyes, Minerva A. M. Zamudio-Aguilar, Luisiana Morales-Zamudio, Tomas Lozano, Fabiola Navarro-Pardo, Saúl Sanchez-Valdez, Guillermo Martinez-Colunga, Sahir Karami, Pierre Lafleur
Publikováno v:
Iranian Polymer Journal. 32:139-149
Autor:
Kaddour Bouazza-Marouf
Publikováno v:
International Journal of Production Research. 32:1754-1755
Autor:
Marielli Elizabeth Ponce-Medina, Saúl Sánchez-Valdés, Marisela Estefanía Ángeles-San Martin, Homero Salas-Papayanopolos, Daniel Eugenio Hernández-Hernández, Tomas Lozano-Ramírez, Shervin Karami, Pierre LaFleur, Ana Beatriz Morales-Cepeda
Publikováno v:
Cogent Engineering, Vol 5, Iss 1 (2018)
Previous studies of Candelilla bagasse fiber (CBF) have demonstrated the improvement of fiber-polymer adhesion; in the present investigation, the CBF was used to reinforce fiber of Polypropylene composites varying the amount of fiber (0, 20 and 30 wt
Externí odkaz:
https://doaj.org/article/4f1ffb53cf3d4c9a8ec75f30af81774f
Publikováno v:
Scopus-Elsevier
MIT web domain
MIT web domain
We present POMCoP, a system for online planning in collaborative domains that reasons about how its actions will affect its understanding of human intentions, and demonstrate its use in building sidekicks for cooperative games. POMCoP plans in belief
Motion planning is a ubiquitous problem that is often a bottleneck in robotic applications. We demonstrate that motion planning problems such as minimum constraint removal, belief-space planning, and visibility-aware motion planning (VAMP) benefit fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::849535af3fda2fd6619bda096438de22
http://arxiv.org/abs/2206.02305
http://arxiv.org/abs/2206.02305
A longstanding objective in classical planning is to synthesize policies that generalize across multiple problems from the same domain. In this work, we study generalized policy search-based methods with a focus on the score function used to guide th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::020ab1402178793376ff324c44e59188
http://arxiv.org/abs/2204.10420
http://arxiv.org/abs/2204.10420
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Anytime motion planners are widely used in robotics. However, the relationship between their solution quality and computation time is not well understood, and thus, determining when to quit planning and start execution is unclear. In this paper, we a
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Robotic planning problems in hybrid state and action spaces can be solved by integrated task and motion planners (TAMP) that handle the complex interaction between motion-level decisions and task-level plan feasibility. TAMP approaches rely on domain