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Stochastic process
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711	Bulletin of the Seismological Society of America, Vol. 102, No. 4, pp. 1583–1592, August 2012, doi: [removed][removed]Were Global M ≥ 8:3 Earthquake Time Intervals Random between 1900 and 2011? by Tom Parsons and E Add to Reading List Source URL: profile.usgs.gov Language: English - Date: 2012-08-17 14:58:18 Earthquake Aftershock Tōhoku earthquake and tsunami Poisson process Richter magnitude scale Normal distribution Statistics Seismology Stochastic processes
712	Telecommunication Systems 21:2–4, 149–171, 2002  2002 Kluwer Academic Publishers. Manufactured in The Netherlands. Queue Lengths and Waiting Times for Multiserver Queues with Abandonment and Retrials AVI MANDELBAU Add to Reading List Source URL: www.princeton.edu Language: English - Date: 2006-04-03 11:07:42 Fluid queue Statistics Stochastic processes Poisson process
713	Bulletin of the Seismological Society of America, Vol. 102, No. 4, pp. 1583–1592, August 2012, doi: [removed][removed]Were Global M ≥ 8:3 Earthquake Time Intervals Random between 1900 and 2011? by Tom Parsons and E Add to Reading List Source URL: walrus.wr.usgs.gov Language: English - Date: 2012-08-16 17:28:45 Earthquake Aftershock Tōhoku earthquake and tsunami Poisson process Richter magnitude scale Normal distribution Statistics Seismology Stochastic processes
714	Learning Distributed Control for Modular Robots Paulina Varshavskaya, Leslie Pack Kaelbling and Daniela Rus MIT CSAIL Cambridge, MA, USA {paulina,lpk,rus}@csail.mit.edu Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2004-06-30 13:22:50 Stochastic control Reinforcement learning Machine learning Markov decision process Self-reconfiguring modular robot Q-learning Robotics Robot Statistics Dynamic programming Markov processes
715	DetH: Approximate Hierarchical Solution of Large Markov Decision Processes∗ Jennifer L. Barry, Leslie Pack Kaelbling, Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02 Add to Reading List Source URL: people.csail.mit.edu Language: English* - Date: 2012-06-11 20:17:47 Dynamic programming Markov processes Stochastic control Optimal control Markov decision process Reinforcement learning Function Macro Automated planning and scheduling Statistics Control theory Mathematics
716	DetH: Approximate Hierarchical Solution of Large Markov Decision Processes∗ Jennifer L. Barry, Leslie Pack Kaelbling, Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02 Add to Reading List Source URL: people.csail.mit.edu Language: English* - Date: 2011-09-29 15:55:17 Dynamic programming Markov processes Stochastic control Optimal control Markov decision process Reinforcement learning Function Macro Automated planning and scheduling Statistics Control theory Mathematics
717	Robust Belief-Based Execution of Manipulation Programs Kaijen Hsiao, Tom´ as Lozano-P´erez, and Leslie Pack Kaelbling Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, {kjh Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2008-12-03 20:20:17 Stochastic control Dynamical system Motion planning Robot Kinematics Normal distribution Mobile robot Statistics Dynamic programming Partially observable Markov decision process
718	Bayesian Nonparametric Learning with semi-Markovian Dynamics by Matthew J Johnson B.S. in Electrical Engineering and Computer Sciences Add to Reading List Source URL: ssg.mit.edu Language: English - Date: 2012-02-01 13:36:21 Hidden Markov models Bayesian statistics Markov models Hidden semi-Markov model Dirichlet process Gibbs sampling Bayesian inference Mixture model Non-parametric statistics Statistics Stochastic processes Statistical inference
719	Artificial Intelligence[removed]–134 Planning and acting in partially observable stochastic domains Leslie Pack Kaelbling a,∗,1,2 , Michael L. Littman b,3 , Anthony R. Cassandra c,1 Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2004-07-01 07:47:55 Stochastic control Markov models Partially observable Markov decision process Markov decision process Reinforcement learning Automated planning and scheduling Markov chain Kalman filter Statistics Markov processes Dynamic programming
720	Hierarchical Solution of Large Markov Decision Processes Jennifer Barry and Leslie Pack Kaelbling and Tom´as Lozano-P´erez MIT Computer Science and Artificial Intelligence Laboratory Cambridge, MA 02139, USA {jbarry,lp Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2010-05-17 16:00:47 Dynamic programming Markov processes Stochastic control Network theory Markov decision process Reinforcement learning Symbol Algorithm Shortest path problem Statistics Mathematics Applied mathematics

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