CSE 434
todorovcs.washington.edu
Areas of interest: 

Intelligent control in biology and engineering

Neuromuscular stochastic optimal control of a tendon-driven index finger model

E. Theodorou, E. Todorov, F. Valero-CuevasAmerican Control Conference , 2011.

Aggregation methods for linearly-solvable MDPs

M. Zhong, E. TodorovWorld Congress of the International Federation of Automatic Control , 2011.

Moving least-squares approximations for linearly-solvable stochastic optimal control problems

M. Zhong, E. TodorovJournal of Control Theory Applications  9 , 2011.

Inverse optimality design for biological movement systems

W. Li, E. Todorov, D. LiuWorld Congress of the International Federation of Automatic Control , 2011.

A unifying framework for linearly-solvable control

K. Dvijotham, E. TodorovUncertainty in Artificial Intelligence , 2011.

Finding the most likely trajectories of optimally-controlled stochastic systems

E. TodorovWorld Congress of the International Federation of Automatic Control , 2011.

High-order local dynamic programming

Y. Tassa, E. TodorovIEEE Adaptive Dynamic Programming and Reinforcement Learning , 2011.

Inverse Optimal Control with Linearly Solvable MDPs

K. Dvijotham, E. TodorovInternational Conference on Machine Learning , 2010.

Stochastic differential dynamic programming

E. Theodorou, Y. Tassa, E. TodorovAmerican Control Conference , 2010.

Position estimation and control of compact BLDC motors based on analog linear Hall effect sensors

A. Simpkins, E. TodorovAmerican Control Conference , 2010.

Identification and control of a pneumatic robot

E. Todorov, C. Hu, A. Simpkins, J. MovellanIEEE BioRob , 2010.

A first optimal control solution for a complex, nonlinear, tendon driven neuromuscular finger model

E. Theodorou, E. Todorov, F. Valero-CuevasASME Summer Bioengineering Conference , 2010.

Inverse optimal control with linearly-solvable MDPs

K. Dvijotham, T. E.International Conference on Machine Learning , 2010.

Policy gradients in linearly-solvable MDPs

E. TodorovAdvances in Neural Information Processing Systems , 2010.

Practical numerical methods for stochastic optimal control of biological systems in continuous time and space

A. Simpkins, E. TodorovIEEE Adaptive Dynamic Programming and Reinforcement Learning , 2009.

Real-time motor control using recurrent neural networks

D. Huh, E. TodorovIEEE Adaptive Dynamic Programming and Reinforcement Learning , 2009.

Structured variability of muscle activations supports the minimal intervention principle of motor control

F. Valero-Cuevas, M. Venkadesan, E. TodorovJournal of Neurophysiology  102 , 2009.

Iterative local dynamic programming

E. Todorov, Y. TassaIEEE Adaptive Dynamic Programming and Reinforcement Learning , 2009.

Efficient computation of optimal actions

TodorovProceedings of the National Academy of Science  106 , 2009.

Hierarchical optimal control of a 7-DOF arm model

D. Liu, E. TodorovIEEE Adaptive Dynamic Programming and Reinforcement Learning , 2009.

Compositionality of optimal control laws

E. TodorovAdvances in Neural Information Processing Systems , 2009.

Eigenfunction approximation methods for linearly-solvable optimal control problems

E. TodorovIEEE Adaptive Dynamic Programming and Reinforcement Learning , 2009.

Optimal trade-off between exploration and exploitation

A. Simpkins, R. Callafon, E. TodorovAmerican Control Conference , 2008.

Parallels between sensory and motor information processing

E. TodorovThe Cognitive Neurosciences, 4th ed.MIT Press , 2008.

General duality between optimal control and estimation

E. TodorovIEEE Conference on Decision and Control , 2008.

State estimation with finite signals-to-noise models via linear matrix inequalities

W. Li, R. Skelton, E. TodorovJournal of Dynamic Systems, Measurement and Control  129 , 2007.

Predicting reaching targets from human EEG

P. Hammon, S. Makeig, E. Poizner, V. SaIEEE Signal Processing Magazine  25 , 2007.

Evidence for the flexible sensorimotor strategies predicted by optimal feedback control

D. Liu, E. TodorovJournal of Neuroscience  27 , 2007.

Optimal control theory

E. TodorovBayesian Brain: Probabilistic Approaches to Neural CodingMIT Press , 2006.

Linearly-solvable Markov decision problems

E. TodorovAdvances in Neural Information Processing Systems , 2006.

Iterative optimal control and estimation design for nonlinear stochastic systems

W. Li, E. TodorovIEEE Conference on Decision and Control , 2006.

Imitiation learning for reaching and grasping in virtual environments

N. Singh, E. TodorovInternational Conference on Development and Learning , 2006.

Towards an integrated systems for estimating multi-joint movement from diverse sensor data

X. Pan, E. Todorov, W. LiIEEE Engineering in Medicine and Biology , 2005.

Hierarchical feedback and learning for multi-joint arm movement control

W. Li, E. Todorov, X. PanIEEE Engineering in Medicine and Biology , 2005.

Estimation and control of systems with multiplicative noise via linear matrix inequalities

W. Li, R. Skelton, E. TodorovAmerican Control Conference , 2005.

Optimality principles in sensorimotor control

E. TodorovNature Neuroscience  7 , 2004.

Iterative linear-quadratic regulator design for nonlinear biological movement systems

W. Li, E. TodorovInternational Conference on Informatics in Control, Automation and Robotics , 2004.

Development of clinician-friendly software for musculoskeletal modeling and control

R. Davoodi, C. Urata, E. Todorov, G. LoebIEEE Engineering in Medicine and Biology , 2004.

Hierarchical optimal control of redundant biomechanical systems

W. Li, E. Todorov, X. PanIEEE Engineering in Medicine and Biology , 2004.

Analysis of the synergies underlying complex hand manipulation

E. Todorov, Z. GhahramaniIEEE Engineering in Medicine and Biology , 2004.

Optimal control methods suitable for biomechanical systems

E. Todorov, W. LiIEEE Engineering in Medicine and Biology , 2003.

Unsupervised learning of sensory-motor primitives

E. Todorov, Z. GhahramaniIEEE Engineering in Medicine and Biology , 2003.

On the role of primary motor cortex in arm movement control

E. TodorovProgress in Motor Control IIIHuman Kinetics , 2003.

A minimal intervention principle for coordinated movement

E. Todorov, M. JordanAdvances in Neural Information Processing Systems , 2003.

Optimal feedback control as a theory of motor coordination

E. Todorov, M. JordanNature Neuroscience  5 , 2002.

Use of virtual environments in motor learning and rehabilitation

M. Holden, E. TodorovHandbook of Virtual EnvironmentsLawrence Erlbaum Associates , 2002.

Cosine tuning minimizes motor errors

E. TodorovNeural Computation  14 , 2002.

A biomechanical model of the partially paralyzed human arm

R. Davoodi, I. Brown, E. Todorov, G. LoebAnnual Conference of the International Functional Electric Stimulation Society , 2002.

One motor cortex, two different views

E. TodorovNature Neuroscience  3 , 2000.

Virtual environment training improves motor performance in two patients with stroke

M. Holden, E. Todorov, J. Callahan, E. BizziNeurology Report  23 , 1999.

Modeling visual cortical contrast adaptation effects

E. Todorov, A. Siapas, D. Somers, S. NelsonComputational Neuroscience , 1997.

Augmented feedback presented in a virtual environment accelerates learning of a difficult motor task

E. Todorov, R. Shadmehr, E. BizziJournal of Motor Behavior  29 , 1997.

A local circuit integration approach to understanding visual cortical receptive fields

D. Somers, E. Todorov, A. SiapasComputational Neuroscience , 1997.

A model of recurrent interactions in primary visual cortex

E. Todorov, A. Siapas, D. SomersAdvances in Neural Information Processing Systems , 1997.

Variable gain control in local cortical circuitry supports context-dependent modulation by long-range connections

D. Somers, L. Toth, E. TodorovLateral Interactions in Cortex - Structure and FunctionOnline Book , 1996.

Factorial learning by clustering features

J. Tenenbaum, E. TodorovAdvances in Neural Information Processing Systems , 1995.

Catastrophic interference in human motor learning

T. Brashers-Krug, R. Shadmehr, E. TodorovAdvances in Neural Information Processing Systems , 1995.