BibSonomy publications for /user/schaul

Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion

schaul — 2008-02-26T12:05:08+01:00

Nate Kohl, and Peter Stone Proceedings of the IEEE International Conference on Robotics and Automation, (May 2004)

Evolving Keepaway Soccer Players through Task Decomposition

schaul — 2008-02-26T12:05:08+01:00

Shimon Whiteson, Nate Kohl, Risto Miikkulainen, and Peter Stone Machine Learning 59(1):5--30 (May 2005)

Hierarchical Policy Gradient Algorithms

schaul — 2008-02-26T12:05:08+01:00

M. Ghavamzadeh, and Sridhar Mahadevan Proceedings of the Twentieth Conference on Machine Learning ICML-2003, (2003)

Reinforcement Learning for RoboCup-Soccer Keepaway

schaul — 2008-02-26T12:05:08+01:00

Peter Stone, Richard S. Sutton, and Gregory Kuhlmann Adaptive Behavior 13(3):165--188 (2005)

Reinforcement learning with long short-term memory

schaul — 2008-02-26T12:05:08+01:00

B. Bakker Advances in Neural Information Processing Syst., 14, (2002)

Natural Actor-Critic

schaul — 2008-02-26T12:05:08+01:00

J. Peters, S. Vijayakumar, and S. Schaal Proceedings of the 16th European Conference on Machine Learning ECML 2005, page 280--291. (2005)

Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation

schaul — 2008-02-26T12:05:08+01:00

Nicol Schraudolph, Jin Yu, and Douglas Aberdeen Advances in Neural Information Processing Systems 18, MIT Press, Cambridge, MA, (2006)

Reinforcement Learning Through Gradient Descent

schaul — 2008-02-26T12:05:08+01:00

L. Baird (1999)

A learning algorithm for continually running fully recurrent networks

schaul — 2008-02-26T12:05:08+01:00

R. J. Williams, and D. Zipser Neural Computation 1(2):270--280 (1989)

Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM

schaul — 2008-02-26T12:05:08+01:00

J. Schmidhuber, F. Gers, and D. Eck Neural Computation 14(9):2039--2041 (2002)

Gradient flow in recurrent nets: the difficulty of learning long-term dependencies

schaul — 2008-02-26T12:05:08+01:00

S. Hochreiter, Y. Bengio, P. Frasconi, and J. Schmidhuber A Field Guide to Dynamical Recurrent Neural Networks, IEEE Press, (2001)

RNN overview

schaul — 2008-02-26T12:05:08+01:00

J. Schmidhuber (2004)

Reinforcement learning and its application to control

schaul — 2008-02-26T12:05:08+01:00

V. Gullapalli (1992)

Two-phase nozzle and hollow core jet experiments

schaul — 2008-02-26T12:05:08+01:00

J. Klockgether, and H. P. Schwefel Proc. 11th Symp. Engineering Aspects of Magnetohydrodynamics, page 141--148. (1970)

Stochastic optimization and the simultaneous perturbation method

schaul — 2008-02-26T12:05:08+01:00

James C. Spall WSC '99: Proceedings of the 31st conference on Winter simulation, page 101--109. New York, NY, USA, ACM, (1999)

Swarm intelligence

schaul — 2008-02-26T12:05:08+01:00

James Kennedy, and Russell C. Eberhart Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, (2001)

Optimization by Simulated Annealing

schaul — 2008-02-26T12:05:08+01:00

S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi Science, Number 4598, 13 May 1983 (1983)

Natural Gradient Works Efficiently in Learning

schaul — 2008-02-26T12:05:08+01:00

S. Amari Neural Computation 10(2):251--276 (1998)

Similarities and differences between policy gradient methods and evolution strategies

schaul — 2008-02-26T12:05:08+01:00

Verena H. Meisner, and Christian Igel To appear in: 16th European Symposium on Artificial Neural Networks ESANN, (2008)

A Tutorial on the Cross-Entropy Method

schaul — 2008-02-26T12:05:08+01:00

P. De Boer, Kroese, S. Mannor, and R. Y. Rubinstein Annals of Operations Research, 134, page 19--67. (2004)