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26th Annual computational neuroscience Meeting (CNS*2017) of the Organization for computational neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC neuroscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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An energy efficient gait trajectory planning algorithm for a seven linked biped robot using movement elements

An energy efficient gait trajectory planning algorithm for a...

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Iranian Conference on Electrical Engineering (ICEE)

作者： AmirHosein KhazeniFard Fariba Bahrami Mehran Emadi Andani Majid Nili Ahmadabadi University of Tehran Tehran Tehran IR Human Motor Control and Computational Neuroscience Laboratory College of Engineering University of Tehran Tehran Iran Department of Biomedical Engineering University of Isfahan Esfahan Iran

In this paper, a computational algorithm is introduced to generate energy efficient gait patterns. Each space cycle of gait has been decomposed to several phases, and boundaries of each phase are called via points. The algorithm uses six universal movement elements [1] together with kinematic information of the physical system at via points. We also developed an optimization procedure to obtain energy efficient kinematic information for the via points and called the new algorithm "optimized-COMAP". The algorithms was used to generate gait patterns for a human like, seven link biped robot. For the joint trajectories of the lower extremities of a optmized-COMAP have been used. Then a desired ZMP trajectory restricted into two upper and lower boundaries has been used to generate upper-body trajectory and to guarantee dynamic balance of the robot. The methodology was evaluated by simulating the model of the biped robot together with a closed loop feedback linearization controller. The proposed planning method can be applied to other mobile robots control systems as a structured pattern generator which just needs initial and final kinematic information of the physical system at via points.

关键词： Trajectory Joints Kinematics Legged locomotion Mathematical model Robot kinematics

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Designing and Modeling of an Index Finger Exoskeleton in Interaction with Post-Stroke Patients' Hand

Designing and Modeling of an Index Finger Exoskeleton in Int...

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Iranian Conference on Biomedical Engineering

作者： Bahare Abdi Fariba Bahrami Zahra Fakhari Majid Nili-Ahmadabadi Human Motor Control and Computational Neuroscience laboratory CIPCE School of Electrical and Computer Engineering College of Engineering University of Tehran Rehabilitation Faculty of Tehran University of Medical Sciences (TUMS) Cognitive Robotic Laboratory CIPCE School of ECE University College of Engineering University of Tehran

ISBN: (纸本)9781467393522

Post-stroke patients usually suffer from lower and upper limbs disorders, which require intense rehabilitation therapies, among which hand function restoration is of a higher significance. This paper introduces the procedure of designing and modeling a novel finger-exoskeleton module (for each finger) in interaction with patients' hand. In this study, our aim is to develop a biomimetic structure that is compatible with anthropomorphic kinematics. Shape memory alloy (SMA) wires were employed to actuate the exoskeleton which makes the system lightweight, compact, and easy to use during daily life activities (DLAs). The overall system was modeled in MATlab Simulink. The simulations show promising results that encourage us to develop and implement the module for clinical trials. Comprehensiveness of the simulation in this paper allows us to further analyze the system by adding new features to the system.

关键词： Rehabilitation Finger exoskeleton Biomimetic Shape memory alloy

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Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015

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LANCET 2016年第10053期388卷 1459-1544页

作者： Wang, Haidong Naghavi, Mohsen Allen, Christine Barber, Ryan M. Bhutta, Zulfiqar A. Carter, Austin Casey, Daniel C. Charlson, Fiona J. Chen, Alan Zian Coates, Matthew M. Coggeshall, Megan Dandona, Lalit Dicker, Daniel J. Erskine, Holly E. Ferrari, Alize J. Fitzmaurice, Christina Foreman, Kyle Forouzanfar, Mohammad H. Fraser, Maya S. Pullman, Nancy Gething, Peter W. Goldberg, Ellen M. Graetz, Nicholas Haagsma, Juanita A. Hay, Simon I. Huynh, Chantal Johnson, Catherine Kassebaum, Nicholas J. Kinfu, Yohannes Kulikoff, Xie Rachel Kutz, Michael Kyu, Hmwe H. Larson, Heidi J. Leung, Janni Liang, Xiaofeng Lim, Stephen S. Lind, Margaret Lozano, Rafael Marquez, Neal Mensah, George A. Mikesell, Joe Mokdad, Ali H. Mooney, Meghan D. Nguyen, Grant Nsoesie, Elaine Pigott, David M. Pinho, Christine Roth, Gregory A. Salomon, Joshua A. Sandar, Logan Silpakit, Naris Sligar, Amber Sorensen, Reed J. D. Stanaway, Jeffrey Steiner, Caitlyn Teeple, Stephanie Thomas, Bernadette A. Troeger, Christopher VanderZanden, Amelia Vollset, Stein Emil Wanga, Valentine Whiteford, Harvey A. Wolock, Timothy Zoeckler, Leo Abate, Kalkidan Hassen Abbafati, Cristiana Abbas, Kaja M. Abd-Allah, Foad Abera, Semaw Ferede Abreu, Daisy M. X. Abu-Raddad, Laith J. Abyu, Gebre Yitayih Achoki, Tom Adelekan, Ademola Lukman Ademi, Zanfina Adou, Arsene Kouablan Adsuar, Jose C. Afanvi, Kossivi Agbelenko Afshin, Ashkan Agardh, Emilie Elisabet Agarwal, Arnav Agrawal, Anurag Kiadaliri, Aliasghar Ahmad Ajala, Oluremi N. Akanda, All Shafqat Akinyemi, Rufus Olusola Akinyemiju, Tomi F. Akseer, Nadia Al Lami, Faris Hasan Alabed, Samer Al-Aly, Ziyad Alam, Khurshid Alam, Noore K. M. Alasfoor, Deena Aldhahri, Saleh Fahed Aldridge, Robert William Alegretti, Miguel Angel Aleman, Alicia V. Alemu, Zewdie Aderaw Alexander, Lily T. Alhabib, Samia Ali, Raghib Alkerwi, Ala'a Alla, Francois Allebeck, Peter Al-Raddadi, Rajaa Alsharif, Ubai Altirkawi, Khalid A. Martin, Elena Alvarez Alvis-Guzman, Nelson Amare, Azmeraw T. Amegah, Adeladza Kofi Ameh, Emmanuel A. Amini, Heresh Ammar, Walid Amro Inst Hlth Metr & Evaluat Seattle WA USA Harborview UW Med Seattle WA USA Harborview Injury Prevent & Res Ctr Seattle WA USA Dept Anesthesiol & Pain Med Seattle WA USA Univ Washington Seattle WA 98195 USA Ctr Excellence Women & Child Hlth Karachi Pakistan Aga Khan Univ Karachi Pakistan Hosp Sick Children Ctr Global Child Hlth Toronto ON Canada Univ Queensland Sch Publ Hlth Brisbane Qld Australia Univ Queensland Sch Dent Brisbane Qld Australia Univ Queensland Brisbane Qld Australia Queensland Ctr Mental Hlth Res Brisbane Qld Australia Ctr Control Chron Condit Gurgaon Haryana India Publ Hlth Fdn India New Delhi India Dept Zool Oxford England NIHR Musculoskeletal Biomed Res Ctr Oxford England Clin Trial Serv Unit Oxford England Nuffield Dept Med Oxford England Univ Oxford Oxford England Univ Med Ctr Erasmus MC Dept Publ Hlth Rotterdam Netherlands Univ Canberra Fac Hlth Ctr Res & Action Publ Hlth Canberra ACT Australia Dept Infect Dis Epidemiol London England London Sch Hyg & Trop Med London England Natl Inst Publ Hlth Cuernavaca Morelos Mexico Natl Ctr Chron & Noncommunicable Dis Control & Pr Beijing Peoples R China Chinese Ctr Dis Control Beijing Peoples R China NHLBI NIH Ctr Translat Res & Implementat Sci Bethesda MD USA Dept Global Hlth & Populat Boston MA USA Harvard T H Chan Sch Publ Hlth Boston MA USA Channing Div Network Med Dept Epidemiol Boston MA USA Brigham & Womens Hosp 75 Francis St Boston MA 02115 USA Harvard Med Sch Boston MA USA Harvard Univ Boston MA 02115 USA Ctr Dis Burden Oslo Norway Norwegian Inst Publ Hlth Oslo Norway Dept Global Publ Hlth & Primary Care Jimma Ethiopia Univ Bergen Bergen Norway Jimma Univ Jimma Ethiopia Univ Roma La Sapienza Rome Italy Virginia Tech Blacksburg VA USA Cairo Univ Dept Neurol Cairo Egypt Sch Publ Hlth Coll Hlth Sci Mekelle Ethiopia Sch Publ Hlth Mekelle Ethiopia Coll Hlth Sci Mekelle Ethiopia Mekelle Univ Mekelle Ethiopia Kilte AwlaeloHealth & Demog Survei

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2

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Distributed Series Elastic Actuator: analysis and simulations

Distributed Series Elastic Actuator: analysis and simulation...

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International Conference on control, Automation and Systems

作者： Hamed Ali Yaghini Bonabi Majid Nili Ahmadabadi Fariba Bahrami Cognitive Robotic Lab. School of Electrical and Computer Engineering College of Engineering University of Tehran Motor Control and Computational Neuroscience Lab School of Electrical and Computer Engineering College of Engineering University of Tehran

ISBN: (纸本)9781467322478

Series elastic actuators (SEA's) have been widely used in rehabilitation robots and haptic devices to provide sufficient compliance as well as safety, among some other properties, for performing interactive tasks. Nevertheless, SEA's suffer from two major drawbacks;namely short bandwidth and limited rendered stiffness. In this paper, we propose a new elastic actuator concept in that a set of spatially distributed and mechanically parallel SEAs, each called a SEA component, are grouped and control a single joint. We call our system distributed series elastic actuator (DSEA). Each SEA component has its own controller but gets its set point from a load distribution system. The analytical and the simulation results show that a DSEA has wider bandwidth and better transient performance in addition to elevated rendered stiffness in comparison to its equivalent SEA. In addition, DSEAs consume less energy and require lower power as well as torque.

关键词： Distributed series elastic actuators Compliant robots Rehabilitation robots

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Proceedings of the Frontiers of Retrovirology Conference 2016

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Retrovirology 2016年第1期13卷 1-40页

作者： Irena Zurnic Sylvia Hütter Nicole Stanke Tobias Kern Fabian Lindel Gesche Gerresheim Martin Hamann Erik Müllers Dirk Lindemann Ute Lehmann Juliane Reh Paul Lesbats Peter Cherepanov Melanie Mann Erik Serrao Alan Engelman Claire Da Silva Santos Kevin Tartour Andrea Cimarelli Rya Burdick Jianbo Chen Jaya Sastri Wei-Shau Hu Vinay Pathak Oliver T. Keppler Patrícia de Sousa-Pereira Hanna-Mari Baldauf Marcel Stern Karine Pradeau Sylvia Eiler Nicolas Levy Marc Ruff Sarah Lennon Sarah Cianferani Stéphane Emiliani Vincent Parissi Sylvie Rato Miguel Munoz Angela Ciuffi Antonio Rausell Amalio Telenti Alexander Zhyvoloup Ian Anderson Chen- Hsuin Lee Ariberto Fassati Anat Melamed Delphine Planas Petronela Ancuta Yuwei Zhang Huicheng Chen Annie Bernier Annie Gosselin Janos Kriston-Vizi Robin Ketteler Andy Merritt Charles Bangham Jocelyn Turpin Anthony Rodari Benoit Van Driessche Mathilde Galais Nadége Delacourt Sylvain Fauquenoy Caroline Vanhulle Anna Kula Carine Van Lint Ernst J. Wolvetang Arsène Burny Olivier Rohr Thijs van Montfort Renee van der Sluis Ben Berkhout Dave Speijer Gang Wang Na Zhao Atze T. Das Mirte Scherpenisse Bo Meng Andrzej Rutkowski Lars Dölken Andrew Lever Neil Berry Claire Ham Neil Almond Hoi Ping Mok Nicholas Norton Axel Fun Jack Hirst Mark Wills Chris Hellmund Harriet Groom Thomas Schuster Benedikt Asbach Ralf Wagner Christine Gross Martina Kalmer Andrea K. Thoma-Kress Norbert Donhauser Sebastian Millen Sandra M. Müller-Schmucker Veit Wiesmann Thomas Wittenberg Jan Gettemans Minghua Li Shan-Lu Liu Eric O. Freed Janis Müller Jan Münch Simone Joas Clement Wesley Gnanadurai Edina Lump Christina M. Stürzel Daniel Sauter Frank Kirchhoff Katharina Mack Kathrin Starz Christina Stürzel Xaver Sewald Nasim Motamedi Pradeep Uchil Ruoxi Pi Christin Herrmann Walther Mothes Mark Ladinsky Pamela Bjorkman Jagadish Beloor Priti Kumar Thomas Murooka Thorsten Mempel Michael Brehm Dale Greiner Erica Parrish Nicholas F. Parrish Beatrice H. Hahn Frederic Bibollet-Ruche Ulrike Sauermann Katharina Töpfer Tina Schultheiss Chris Molecular Virology and Gene Therapy Molecular Medicine Leuven Belgium Molecular Virology Technical University Dresden Dresden Germany Center for Regenerative Therapies Dresden Dresden Germany Potsdam University Potsdam Germany The Francis Crick Institute London Great Britain Institute of Clinical and Molecular Virology Friedrich-Alexander-Universität Erlangen-Nuremberg Erlangen Germany Dana Farber Cancer Institute Boston MA United States CIRI Lyon France National Cancer Institute Frederick MD United States Virology Max von Pettenkofer-Institut LMU Munich Munich Germany Institute of Medical Virology University of Frankfurt Frankfurt a. M. Germany German Center for Infection Research Munich Germany Institute of Medical Virology University Hospital Frankfurt Frankfurt a. M. Germany CIBIO/InBIO University of Porto Vairão Portugal Faculty of Sciences University of Porto Porto Portugal Virology Max von Pettenkofer Institute LMU Munich Germany Institute for Medical Virology Frankfurt a. M. Germany Integrative structural Biology IGBMC Illkirch France Institut Pluridisciplinaire Hubert Curien Strasbourg France Institut Cochin Paris France CNRS UMR5234 MFP Lab Bordeaux France Associated International Laboratory (LIA) Microbiology and Immunology CNRS/Université de Bordeaux/Heinrich Pette Institute-Leibniz Institute for Experimental Virology Bordeaux/Hamburg France Institute of Microbiology University Hospital Center and University of Lausanne Lausanne Switzerland Imagine Institute Paris Descartes University Paris France J. Craig Venter Institute La Jolla CA United States Infection University College London London Great Britain Medicine Imperial College London Great Britain Microbiology & Infection University of Montreal Montreal Great Britain CRCHUM Montreal Canada University College London LMCB London Great Britain MRC Technology Centre for Therapeutic Discovery London Great Britain Section of Virology Department of Medicine Imperial Co

Oral presentationsSession 1: Entry & uncoatingO1 Host cell polo-like kinases (PLKs) promote early prototype foamy virus (PFV) replicationIrena Zurnic, Sylvia Hütter, Ute Lehmann, Nicole Stanke, Juliane Re... 详细信息

Oral presentations

Session 1: Entry & uncoating

O1 Host cell polo-like kinases (PLKs) promote early prototype foamy virus (PFV) replication

Irena Zurnic, Sylvia Hütter, Ute Lehmann, Nicole Stanke, Juliane Reh, Tobias Kern, Fabian Lindel, Gesche Gerresheim, Martin Hamann, Erik Müllers, Paul Lesbats, Peter Cherepanov, Erik Serrao, Alan Engelman, Dirk Lindemann

O2 A novel entry/uncoating assay reveals the presence of at least two species of viral capsids during synchronized HIV-1 infection

Claire Da Silva Santos, Kevin Tartour, Andrea Cimarelli

O3 Dynamics of nuclear envelope association and nuclear import of HIV-1 complexes

Rya Burdick, Jianbo Chen, Jaya Sastri, Wei-Shau Hu, Vinay Pathak

O4 human papillomavirus protein E4 potently enhances the susceptibility to HIV infection

Oliver T. Keppler

Session 2: Reverse transcription & integration

O5 Structure and function of HIV-1 integrase post translational modifications

Karine Pradeau, Sylvia Eiler, Nicolas Levy, Sarah Lennon, Sarah Cianferani, Stéphane Emiliani, Marc Ruff

O6 Regulation of retroviral integration by RNA polymerase II associated factors and chromatin structure

Vincent Parissi

Session 3: Transcription and latency

O7 A novel single-cell analysis pipeline to identify specific biomarkers of HIV permissiveness

Sylvie Rato, Antonio Rausell, Miguel Munoz, Amalio Telenti, Angela Ciuffi

O8 A capsid-dependent integration program linking T cell activation to HIV-1 gene expression

Alexander Zhyvoloup, Anat Melamed, Ian Anderson, Delphine Planas, Janos Kriston-Vizi, Robin Ketteler, Chen-Hsuin Lee, Andy Merritt, Petronela Ancuta, Charles Bangham, Ariberto Fassati

O9 Characterisation of new RNA polymerase III and RNA polymerase II transcriptional promoters in the Bovine Leukemia Virus genome

Anthony Rodari, Benoit Van Driessche, Mathilde Galais, Nadége Delacourt, Sylv

关键词： human Immunodeficiency Virus Infection Simian Immunodeficiency Virus Feline Immunodeficiency Virus Bovine Leukemia Virus Prototype Foamy Virus

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An iterative path integral stochastic optimal control approach for learning robotic tasks

An iterative path integral stochastic optimal control approa...

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作者： Theodorou, Evangelos Stulp, Freek Buchli, Jonas Schaal, Stefan Computational Learning and Motor Control Lab. University of Southern California United States Department of Advanced Robotics Italian Institute of Technology Italy ATR Computational Neuroscience Laboratories Kyoto 619-0288 Japan

ISBN: (纸本)9783902661937

Recent work on path integral stochastic optimal control theory Theodorou et al. (2010a);Theodorou (2011) has shown promising results in planning and control of nonlinear systems in high dimensional state spaces. The path integral control framework relies on the transformation of the nonlinear Hamilton Jacobi Bellman (HJB) partial differential equation (PDE) into a linear PDE and the approximation of its solution via the use of the Feynman Kac lemma. In this work, we are reviewing the generalized version of path integral stochastic optimal control formalism Theodorou et al. (2010a), used for optimal control and planing of stochastic dynamical systems with state dependent control and diffusion matrices. Moreover we present the iterative path integral control approach, the so called Policy Improvement with Path Integrals or (PI 2) which is capable of scaling in high dimensional robotic control problems. Furthermore we present a convergence analysis of the proposed algorithm and we apply the proposed framework to a variety of robotic tasks. Finally with the goal to perform locomotion the iterative path integral control is applied for learning nonlinear limit cycle attractors with adjustable land scape. © 2011 IFAC.

关键词： Iterative methods

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An Iterative Path Integral Stochastic Optimal control Approach for Learning Robotic Tasks

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IFAC Proceedings Volumes 2011年第1期44卷 11594-11601页

作者： Evangelos Theodorou Freek Stulp Jonas Buchli Stefan Schaal Computational Learning and Motor Control Lab University of Southern California USA Department of Advanced Robotics Italian Institute of Technology ATR Computational Neuroscience Laboratories Kyoto 619-0288 Japan

Abstract Recent work on path integral stochastic optimal control theory Theodorou et al. (2010a); Theodorou (2011) has shown promising results in planning and control of nonlinear systems in high dimensional state spaces. The path integral control framework relies on the transformation of the nonlinear Hamilton Jacobi Bellman (HJB) partial differential equation (PDE) into a linear PDE and the approximation of its solution via the use of the Feynman Kac lemma. In this work, we are reviewing the generalized version of path integral stochastic optimal control formalism Theodorou et al. (2010a), used for optimal control and planing of stochastic dynamical systems with state dependent control and diffusion matrices. Moreover we present the iterative path integral control approach, the so called P olicy I mprovement with P ath I ntegrals or (PI 2 ) which is capable of scaling in high dimensional robotic control problems. Furthermore we present a convergence analysis of the proposed algorithm and we apply the proposed framework to a variety of robotic tasks. Finally with the goal to perform locomotion the iterative path integral control is applied for learning nonlinear limit cycle attractors with adjustable land scape.

关键词： Path Integrals Stochastic Optimal control Robotics

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Stochastic differential dynamic programming

Stochastic differential dynamic programming

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作者： Theodorou, Evangelos Tassa, Yuval Todorov, Emo Departments of Computer Science and Neuroscience Computational Learning and Motor Control Lab. University of Southern California United States Interdisciplinary Center for Neural Computation Hebrew University Jerusalem Israel Department of Computer Science and Engineering University of Washington Seattle WA United States

ISBN: (纸本)9781424474264

Although there has been a significant amount of work in the area of stochastic optimal control theory towards the development of new algorithms, the problem of how to control a stochastic nonlinear system remains an open research topic. Recent iterative linear quadratic optimal control methods iLQG [1], [2] handle control and state multiplicative noise while they are derived based on first order approximation of dynamics. On the other hand, methods such as Differential Dynamic Programming expand the dynamics up to the second order but so far they can handle nonlinear systems with additive noise. In this work we present a generalization of the classic Differential Dynamic Programming algorithm. We assume the existence of state and control multiplicative process noise, and proceed to derive the second-order expansion of the cost-to-go. We find the correction terms that arise from the stochastic assumption. Despite having quartic and cubic terms in the initial expression, we show that these vanish, leaving us with the same quadratic structure as standard DDP. © 2010 AACC.

关键词： Additive noise

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Stochastic Differential Dynamic Programming

Stochastic Differential Dynamic Programming

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American control Conference

作者： Evangelos Theodorou Yuval Tassa Emo Todorov Computational Learning and Motor Control Lab Departments of Computer Science and Neuroscience University of Southern California Interdisciplinary Center for Neural Computation Hebrew University Jerusalem Israel Department of Computer Science and Engineering and the Department of Applied Mathematics University of Washington Seattle WA

ISBN: (纸本)9781424474264

关键词： dynamic programming theory of optimal control multiplicative noise Quartic stochastic derivative Additive noise correct entry dynamics Work area Handles

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