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4Natural Gradient Works Efficiently in Learning
S. Amari. Neural Computation, 10 (2): 251–276 (1998)
11 years ago by @wittawatj
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3A stochastic reinforcement learning algorithm for learning real-valued functions
V. Gullapalli. Neural Networks, 3 (6): 671--692 (1990)
17 years ago by @huuhau
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3PEGASUS:A policy search method for large MDPs and POMDPs
A. Ng, and M. Jordan. Proceedings of Uncertainty in Artificial Intelligence (UAI) 2000, page 406--415. (2000)
17 years ago by @idsia
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2Direct Gradient-Based Reinforcement Learning
J. Baxter, and P. Bartlett. (1999)
17 years ago by @idsia
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2Policy-Gradient Algorithms for Partially Observable Markov Decision Processes
D. Aberdeen. Australian National University, (2003)
17 years ago by @idsia
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2Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution
I. Rechenberg. TU Berlin, (1971)
17 years ago by @idsia
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2Policy Gradient Methods for Reinforcement Learning with Function Approximation
R. Sutton, D. Mcallester, S. Singh, and Y. Mansour. (2001)
17 years ago by @idsia
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2Actor-Critic Algorithms
V. Konda, and J. Tsitsiklis. (2001)
17 years ago by @idsia
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3Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion
N. Kohl, and P. Stone. Proceedings of the IEEE International Conference on Robotics and Automation, (May 2004)
17 years ago by @idsia
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2Evolving Keepaway Soccer Players through Task Decomposition
S. Whiteson, N. Kohl, R. Miikkulainen, and P. Stone. Machine Learning, 59 (1): 5--30 (May 2005)
17 years ago by @idsia
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3Hierarchical Policy Gradient Algorithms
M. Ghavamzadeh, and S. Mahadevan. Proceedings of the Twentieth Conference on Machine Learning (ICML-2003), (2003)
17 years ago by @idsia
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3Reinforcement Learning for RoboCup-Soccer Keepaway
P. Stone, R. Sutton, and G. Kuhlmann. Adaptive Behavior, 13 (3): 165--188 (2005)
17 years ago by @idsia
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2Keepaway Soccer: From Machine Learning Testbed to Benchmark
P. Stone, G. Kuhlmann, Matthew, and Y. Liu. RoboCup-2005: Robot Soccer World Cup IX, Springer Verlag, Berlin, (2006)
17 years ago by @idsia
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2Biped dynamic walking using reinforcement learning
H. Benbrahim, and J. Franklin. Robotics and Autonomous Systems Journal, (1997)
17 years ago by @idsia
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3Autonomous Helicopter Flight via Reinforcement Learning.
A. Ng, H. Kim, M. Jordan, and S. Sastry. NIPS, MIT Press, (2003)
17 years ago by @idsia
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5Advances in Neural Information Processing Systems 16 Neural Information Processing Systems, NIPS 2003, December 8-13, 2003, Vancouver and Whistler, British Columbia, Canada
S. Thrun, L. Saul, and B. Schölkopf (Eds.) NIPS 2004, MIT Press, (2004)
17 years ago by @idsia
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7Simple statistical gradient-following algorithms for connectionist reinforcement learning
R. Williams. Machine Learning, (1992)
17 years ago by @idsia
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7Learning Finite-State Controllers for Partially Observable Environments
N. Meuleau, L. Peshkin, K. Kim, and L. Kaelbling. Proc. Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI '99). Morgan Kaufmann, page 427--436. (1999)
17 years ago by @idsia
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2Reinforcement Learning for Continuous Action using Stochastic Gradient Ascent
H. Kimura, and S. Kobayashi. (1998)
17 years ago by @idsia
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5Learning Without State-Estimation in Partially Observable Markovian Decision Processes
S. Singh, T. Jaakkola, and M. Jordan. International Conference on Machine Learning, page 284--292. (1994)
17 years ago by @idsia
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2Localizing Policy Gradient Estimates to Action Transitions
G. Grudic, and L. Ungar. Proc. 17th International Conf. on Machine Learning, page 343--350. Morgan Kaufmann, San Francisco, CA, (2000)
17 years ago by @idsia
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7Reinforcement learning with long short-term memory
B. Bakker. Advances in Neural Information Processing Syst., 14, (2002)
17 years ago by @idsia
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5Natural Actor-Critic
J. Peters, S. Vijayakumar, and S. Schaal. Proceedings of the 16th European Conference on Machine Learning (ECML 2005), page 280--291. (2005)
17 years ago by @idsia
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3Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation
N. Schraudolph, J. Yu, and D. Aberdeen. Advances in Neural Information Processing Systems 18, MIT Press, Cambridge, MA, (2006)
17 years ago by @idsia
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3Reinforcement Learning Through Gradient Descent
L. Baird. (1999)
17 years ago by @idsia
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4Evolving neural network controllers for unstable systems
A. Wieland. Proceedings of the International Joint Conference on Neural Networks (Seattle, WA), page 667--673. Piscataway, NJ: IEEE, (1991)
17 years ago by @idsia
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3Turing Computability with Neural Nets
H. Siegelmann, and E. Sontag. Applied Mathematics Letters, 4 (6): 77--80 (1991)
17 years ago by @idsia
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4Back propagation through time: What it does and how to do it.
P. Werbos. Proceedings of the IEEE, 78, page 1550--1560. (1990)
17 years ago by @idsia
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3A learning algorithm for continually running fully recurrent networks
R. Williams, and D. Zipser. Neural Computation, 1 (2): 270--280 (1989)
17 years ago by @idsia
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4Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM
J. Schmidhuber, F. Gers, and D. Eck. Neural Computation, 14 (9): 2039--2041 (2002)
17 years ago by @idsia
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6Gradient flow in recurrent nets: the difficulty of learning long-term dependencies
S. Hochreiter, Y. Bengio, P. Frasconi, and J. Schmidhuber. A Field Guide to Dynamical Recurrent Neural Networks, IEEE Press, (2001)
17 years ago by @idsia
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2RNN overview
J. Schmidhuber. (2004)
17 years ago by @idsia
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2Reinforcement learning and its application to control
V. Gullapalli. (1992)
17 years ago by @idsia
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6TORCS, The Open Racing Car Simulator.
Torcs. (2007)
17 years ago by @idsia
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2Linear quadradic control: an introduction
P. Dorato, C. Abdallah, and V. Cerone. Prentice Hall, (1995)
17 years ago by @idsia
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3A stochastic reinforcement learning algorithm for learning real-valued functions
V. Gullapalli. Neural Networks, 3 (6): 671--692 (1990)
17 years ago by @idsia
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2Toward effective combination of off-line and on-line training in ADP framework
D. Prokhorov. Proceedings of the IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL), (2007)
17 years ago by @idsia
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2Learning to Trade via Direct Reinforcement
J. Moody, and M. Saffell. IEEE Transactions on Neural Networks, 12 (4): 875--889 (July 2001)
17 years ago by @idsia
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2Solving partially observable reinforcement learning problems with recurrent neural networks
A. Schäfer, and S. Udluft. (2005)
17 years ago by @idsia
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3Solving Non-Markovian Control Tasks with Neuroevolution
F. Gomez, and R. Miikkulainen. Proc. IJCAI 99, Denver, CO, Morgan Kaufman, (1999)
17 years ago by @idsia
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2Theoretical Framework for Comparing Several Stochastic Optimization Approaches
J. Spall, S. Hill, and D. Stark. Probabilistic and Randomized Methods for Design under Uncertainty, (2006)
17 years ago by @idsia
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2Two-phase nozzle and hollow core jet experiments
J. Klockgether, and H. Schwefel. Proc. 11th Symp. Engineering Aspects of Magnetohydrodynamics, page 141--148. (1970)
17 years ago by @idsia
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3Stochastic optimization and the simultaneous perturbation method
J. Spall. WSC '99: Proceedings of the 31st conference on Winter simulation, page 101--109. New York, NY, USA, ACM, (1999)
17 years ago by @idsia
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4Swarm intelligence
J. Kennedy, and R. Eberhart. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, (2001)
17 years ago by @idsia
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17Optimization by Simulated Annealing
S. Kirkpatrick, C. Gelatt, and M. Vecchi. Science, Number 4598, 13 May 1983, (1983)
17 years ago by @idsia
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4Natural Gradient Works Efficiently in Learning
S. Amari. Neural Computation, 10 (2): 251--276 (1998)
17 years ago by @idsia
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8Evolution Strategies: A Comprehensive Introduction
H. Beyer, and H. Schwefel. Natural Computing: an international journal, 1 (1): 3--52 (2002)
17 years ago by @idsia
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2Toward a Theory of Evolution Strategies: Self-Adaptation
H. Beyer. Evolutionary Computation, 3 (3): 311--347 (1996)
17 years ago by @idsia
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2Similarities and differences between policy gradient methods and evolution strategies
V. Meisner, and C. Igel. To appear in: 16th European Symposium on Artificial Neural Networks (ESANN), (2008)
17 years ago by @idsia
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2A Tutorial on the Cross-Entropy Method
P. Boer, Kroese, S. Mannor, and R. Rubinstein. Annals of Operations Research, 134, page 19--67. (2004)
17 years ago by @idsia
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6The Cross-Entropy Method: A Unified Approach to Monte Carlo Simulation, Randomized Optimization and Machine Learning
Rubinstein, and D. Kroese. Springer-Verlag, (2004)
17 years ago by @idsia
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3Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion
N. Kohl, and P. Stone. Proceedings of the IEEE International Conference on Robotics and Automation, (May 2004)
17 years ago by @schaul
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2Evolving Keepaway Soccer Players through Task Decomposition
S. Whiteson, N. Kohl, R. Miikkulainen, and P. Stone. Machine Learning, 59 (1): 5--30 (May 2005)
17 years ago by @schaul
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3Hierarchical Policy Gradient Algorithms
M. Ghavamzadeh, and S. Mahadevan. Proceedings of the Twentieth Conference on Machine Learning (ICML-2003), (2003)
17 years ago by @schaul
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3Reinforcement Learning for RoboCup-Soccer Keepaway
P. Stone, R. Sutton, and G. Kuhlmann. Adaptive Behavior, 13 (3): 165--188 (2005)
17 years ago by @schaul
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7Reinforcement learning with long short-term memory
B. Bakker. Advances in Neural Information Processing Syst., 14, (2002)
17 years ago by @schaul
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5Natural Actor-Critic
J. Peters, S. Vijayakumar, and S. Schaal. Proceedings of the 16th European Conference on Machine Learning (ECML 2005), page 280--291. (2005)
17 years ago by @schaul
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3Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation
N. Schraudolph, J. Yu, and D. Aberdeen. Advances in Neural Information Processing Systems 18, MIT Press, Cambridge, MA, (2006)
17 years ago by @schaul
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3Reinforcement Learning Through Gradient Descent
L. Baird. (1999)
17 years ago by @schaul
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3A learning algorithm for continually running fully recurrent networks
R. Williams, and D. Zipser. Neural Computation, 1 (2): 270--280 (1989)
17 years ago by @schaul
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4Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM
J. Schmidhuber, F. Gers, and D. Eck. Neural Computation, 14 (9): 2039--2041 (2002)
17 years ago by @schaul
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6Gradient flow in recurrent nets: the difficulty of learning long-term dependencies
S. Hochreiter, Y. Bengio, P. Frasconi, and J. Schmidhuber. A Field Guide to Dynamical Recurrent Neural Networks, IEEE Press, (2001)
17 years ago by @schaul
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2RNN overview
J. Schmidhuber. (2004)
17 years ago by @schaul
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2Reinforcement learning and its application to control
V. Gullapalli. (1992)
17 years ago by @schaul
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2Two-phase nozzle and hollow core jet experiments
J. Klockgether, and H. Schwefel. Proc. 11th Symp. Engineering Aspects of Magnetohydrodynamics, page 141--148. (1970)
17 years ago by @schaul
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3Stochastic optimization and the simultaneous perturbation method
J. Spall. WSC '99: Proceedings of the 31st conference on Winter simulation, page 101--109. New York, NY, USA, ACM, (1999)
17 years ago by @schaul
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4Swarm intelligence
J. Kennedy, and R. Eberhart. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, (2001)
17 years ago by @schaul
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17Optimization by Simulated Annealing
S. Kirkpatrick, C. Gelatt, and M. Vecchi. Science, Number 4598, 13 May 1983, (1983)
17 years ago by @schaul
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4Natural Gradient Works Efficiently in Learning
S. Amari. Neural Computation, 10 (2): 251--276 (1998)
17 years ago by @schaul
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2Similarities and differences between policy gradient methods and evolution strategies
V. Meisner, and C. Igel. To appear in: 16th European Symposium on Artificial Neural Networks (ESANN), (2008)
17 years ago by @schaul
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2A Tutorial on the Cross-Entropy Method
P. Boer, Kroese, S. Mannor, and R. Rubinstein. Annals of Operations Research, 134, page 19--67. (2004)
17 years ago by @schaul
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6The Cross-Entropy Method: A Unified Approach to Monte Carlo Simulation, Randomized Optimization and Machine Learning
Rubinstein, and D. Kroese. Springer-Verlag, (2004)
17 years ago by @schaul
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3PEGASUS:A policy search method for large MDPs and POMDPs
A. Ng, and M. Jordan. Proceedings of Uncertainty in Artificial Intelligence (UAI) 2000, page 406--415. (2000)
17 years ago by @schaul
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2Direct Gradient-Based Reinforcement Learning
J. Baxter, and P. Bartlett. (1999)
17 years ago by @schaul
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2Policy-Gradient Algorithms for Partially Observable Markov Decision Processes
D. Aberdeen. Australian National University, (2003)
17 years ago by @schaul
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2Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution
I. Rechenberg. TU Berlin, (1971)
17 years ago by @schaul
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2Policy Gradient Methods for Reinforcement Learning with Function Approximation
R. Sutton, D. Mcallester, S. Singh, and Y. Mansour. (2001)
17 years ago by @schaul
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2Actor-Critic Algorithms
V. Konda, and J. Tsitsiklis. (2001)
17 years ago by @schaul
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2Keepaway Soccer: From Machine Learning Testbed to Benchmark
P. Stone, G. Kuhlmann, Matthew, and Y. Liu. RoboCup-2005: Robot Soccer World Cup IX, Springer Verlag, Berlin, (2006)
17 years ago by @schaul
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2Biped dynamic walking using reinforcement learning
H. Benbrahim, and J. Franklin. Robotics and Autonomous Systems Journal, (1997)
17 years ago by @schaul
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3Autonomous Helicopter Flight via Reinforcement Learning.
A. Ng, H. Kim, M. Jordan, and S. Sastry. NIPS, MIT Press, (2003)
17 years ago by @schaul
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5Advances in Neural Information Processing Systems 16 Neural Information Processing Systems, NIPS 2003, December 8-13, 2003, Vancouver and Whistler, British Columbia, Canada
S. Thrun, L. Saul, and B. Schölkopf (Eds.) NIPS 2004, MIT Press, (2004)
17 years ago by @schaul
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7Simple statistical gradient-following algorithms for connectionist reinforcement learning
R. Williams. Machine Learning, (1992)
17 years ago by @schaul
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7Learning Finite-State Controllers for Partially Observable Environments
N. Meuleau, L. Peshkin, K. Kim, and L. Kaelbling. Proc. Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI '99). Morgan Kaufmann, page 427--436. (1999)
17 years ago by @schaul
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2Reinforcement Learning for Continuous Action using Stochastic Gradient Ascent
H. Kimura, and S. Kobayashi. (1998)
17 years ago by @schaul
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5Learning Without State-Estimation in Partially Observable Markovian Decision Processes
S. Singh, T. Jaakkola, and M. Jordan. International Conference on Machine Learning, page 284--292. (1994)
17 years ago by @schaul
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2Localizing Policy Gradient Estimates to Action Transitions
G. Grudic, and L. Ungar. Proc. 17th International Conf. on Machine Learning, page 343--350. Morgan Kaufmann, San Francisco, CA, (2000)
17 years ago by @schaul
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4Evolving neural network controllers for unstable systems
A. Wieland. Proceedings of the International Joint Conference on Neural Networks (Seattle, WA), page 667--673. Piscataway, NJ: IEEE, (1991)
17 years ago by @schaul
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3Turing Computability with Neural Nets
H. Siegelmann, and E. Sontag. Applied Mathematics Letters, 4 (6): 77--80 (1991)
17 years ago by @schaul
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4Back propagation through time: What it does and how to do it.
P. Werbos. Proceedings of the IEEE, 78, page 1550--1560. (1990)
17 years ago by @schaul
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6TORCS, The Open Racing Car Simulator.
Torcs. (2007)
17 years ago by @schaul
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2Linear quadradic control: an introduction
P. Dorato, C. Abdallah, and V. Cerone. Prentice Hall, (1995)
17 years ago by @schaul
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3A stochastic reinforcement learning algorithm for learning real-valued functions
V. Gullapalli. Neural Networks, 3 (6): 671--692 (1990)
17 years ago by @schaul
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2Toward effective combination of off-line and on-line training in ADP framework
D. Prokhorov. Proceedings of the IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL), (2007)
17 years ago by @schaul
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2Learning to Trade via Direct Reinforcement
J. Moody, and M. Saffell. IEEE Transactions on Neural Networks, 12 (4): 875--889 (July 2001)
17 years ago by @schaul
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2Solving partially observable reinforcement learning problems with recurrent neural networks
A. Schäfer, and S. Udluft. (2005)
17 years ago by @schaul
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3Solving Non-Markovian Control Tasks with Neuroevolution
F. Gomez, and R. Miikkulainen. Proc. IJCAI 99, Denver, CO, Morgan Kaufman, (1999)
17 years ago by @schaul
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2Theoretical Framework for Comparing Several Stochastic Optimization Approaches
J. Spall, S. Hill, and D. Stark. Probabilistic and Randomized Methods for Design under Uncertainty, (2006)
17 years ago by @schaul
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8Evolution Strategies: A Comprehensive Introduction
H. Beyer, and H. Schwefel. Natural Computing: an international journal, 1 (1): 3--52 (2002)
17 years ago by @schaul
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2Toward a Theory of Evolution Strategies: Self-Adaptation
H. Beyer. Evolutionary Computation, 3 (3): 311--347 (1996)
17 years ago by @schaul
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