For robot control, Stochastic roadmap simulation[1] is inspired by probabilistic roadmap[2] methods (PRM) developed for robot motion planning.
The main idea of these methods is to capture the connectivity of a geometrically complex high-dimensional space by constructing a graph of local paths connecting points randomly sampled from that space. A roadmap G = (V,E) is a directed graph. Each vertex v is a randomly sampled conformation in C. Each (directed) edge from vertex vi to vertex vj carries a weight Pij , which represents the probability that the molecule will move to conformation vj , given that it is currently at vi. The probability Pij is 0 if there is no edge from vi to vj. Otherwise, it depends on the energy difference between conformations.
Stochastic roadmap simulation is used to explore the kinetics of molecular motion by simultaneously examining multiple pathways in the roadmap. Ensemble properties of molecular motion (e.g., probability of folding (PFold), escape time in ligand-protein binding) is computed efficiently and accurately with stochastic roadmap simulation. PFold values are computed using the first step analysis of Markov chain theory.
^Apaydin, M. S.; Brutlag, D. L.; Guestrin, C.; Hsu, D.; Latombe, J.-C. (2003), "Stochastic roadmap simulation: an efficient representation and algorithm for analyzing molecular motion", Computational Biology, 10 (3–4): 257–281, doi:10.1145/565196.565199, PMID 12935328, S2CID 2536409.
^Kavraki, L. E.; Svestka, P.; Latombe, J.-C.; Overmars, M. H. (1996), "Probabilistic roadmaps for path planning in high-dimensional configuration spaces", IEEE Transactions on Robotics and Automation, 12 (4): 566–580, CiteSeerX 10.1.1.19.6316, doi:10.1109/70.508439.
and 24 Related for: Stochastic roadmap simulation information
For robot control, Stochasticroadmapsimulation is inspired by probabilistic roadmap methods (PRM) developed for robot motion planning. The main idea...
collapse and resist strip considerations. Due to stochastic considerations, the IRDS 2022 lithography roadmap now acknowledges increasing doses for smaller...
Mann Steven M. LaValle Stewart platform Stochastic diffusion search StochasticRoadmapSimulationStochastic semantic analysis Strong AI (disambiguation)...
of the individual in a digital computer. The computer would then run a simulation of the brain's information processing, such that it would respond in essentially...
generation is central to simulations, cryptographic applications, and statistical analysis. These numbers form the basis for simulations, model testing, and...
applied to various fields such as meteorology, physiology, and finance. Stochastic computing is a method of computation that represents continuous values...
Business Intelligence (OBIEE) Oracle Crystal Ball – enables stochastic forecasting and simulation using spreadsheet models Oracle Discoverer Data hubs Oracle...
process can be simulated in a computer using quantum Monte Carlo (or other stochastic technique), and thus obtain a heuristic algorithm for finding the ground...
Pseudospectral optimal control Pursuit-evasion games Sliding mode control SNOPT Stochastic control Trajectory optimization Ross, Isaac (2015). A primer on Pontryagin's...
Clinical Trials: How Computer Simulation Will Transform The Biomedical Industry An international research and development roadmap for an industry-driven initiative"...
Gruyter. ISBN 978-3-11-013863-4. MR 1291393. Rissanen, Jorma (1989). Stochastic Complexity in Statistical Inquiry. Series in Computer Science. Vol. 15...
data-driven methods for nonlinear system prediction include the use of stochastic models such as the autoregressive (AR) model, the threshold AR model,...
PMC 299893. PMID 13940312. Hoffmann, Geoffrey W. (October 1975). "The Stochastic Theory of the Origin of the Genetic Code". Annual Review of Physical Chemistry...
1997.9.8.1735. ISSN 0899-7667. PMID 9377276. S2CID 1915014. "Semantic Web roadmap". W3.org. Archived from the original on 6 December 2003. Retrieved 24 November...
"Artificial versus biological intelligence in the Cosmos: clues from a stochastic analysis of the Drake equation". International Journal of Astrobiology...
National Electric Delivery Technologies Roadmap is the implementation document for the Grid 2030 vision. The Roadmap outlines the key issues and challenges...
learning and optimization 1993 Miron Abramovici For contributions to fault simulation and automatic test generation algorithms for VLSI circuits. 2016 David...
By the mid-2000s scientific attention began to flourish. Nanotechnology roadmaps centered on atomically precise manipulation of matter and discussed existing...
under uncertainty are called influence diagrams. A Gaussian process is a stochastic process in which every finite collection of the random variables in the...
methodologies 2008 Michael Fu For contributions to stochastic gradient estimation and simulation optimization 2008 Paolo Gargini For leadership in the...
Intel. Manipatruni, Lipson and collaborators at Intel have projected a roadmap that required the use of Silicon micro-ring modulators to meet the bandwidth...
obvious. Real data is always finite, and so its study requires us to take stochasticity into account. Statistical analysis gives us the ability to separate...
population-based trial-and-error problem-solvers with a metaheuristic or stochastic optimization character. executable Causes a computer "to perform indicated...
vertical column) and Klaus Hasselmann (developed a model incorporating stochastics (chaotic systems) and identifying human "fingerprints" in climatic effects)...
Global Information