Value Function Approximation Publications

Publications in Value Function Approximation

Explore the most influential research papers and scholarly works that have shaped Value Function Approximation. Use the concept filter below to focus on a specific sub-area of research.

Value Function Approximation

1.1K

Publications

79.6K

Citations

Showing yearly statistics from 2000-2026.

Page 1

	Year	Citations
Playing Atari with Deep Reinforcement Learning Volodymyr Mnih, Koray Kavukcuoglu, David Silver, arXiv (Cornell University) Artificial IntelligenceConvolutional Neural NetworkReward HackingEngineeringMachine Learning	2013	5.1K
A direct adaptive method for faster backpropagation learning: the RPROP algorithm Martin Riedmiller, Heinrich Braun IEEE International Conference on Neural Networks Artificial IntelligenceIncremental LearningEngineeringMachine LearningRprop Algorithm	2002	3.9K
Addressing Function Approximation Error in Actor-Critic Methods Scott Fujimoto, Herke van Hoof, David Meger arXiv (Cornell University) Artificial IntelligenceNumerical AnalysisEngineeringMachine LearningValue Function Approximation	2018	2.4K
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning Stefan Elfwing, Eiji Uchibe, Kenji Doya Neural Networks Artificial IntelligenceEngineeringMachine LearningNeural Networks (Machine Learning)Value Function Approximation	2018	1.8K
Teaching–Learning-Based Optimization: An optimization method for continuous non-linear large scale problems R. Venkata Rao, Vimal Savsani, D. P. Vakharia Information Sciences Numerical AnalysisEngineeringMachine LearningContinuous OptimizationOptimization Method	2011	1.8K
High-Dimensional Continuous Control Using Generalized Advantage Estimation John Schulman, Philipp Moritz, Sergey Levine, arXiv (Cornell University) Artificial IntelligenceControl StrategyEngineeringMachine LearningData Science	2015	1.7K
Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition Tom Dietterich Journal of Artificial Intelligence Research Artificial IntelligenceEngineeringMachine LearningAutomated ReasoningGame Theory	2000	1.4K
Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof A. Al-Tamimi, Frank L. Lewis, Murad Abu-Khalaf IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) Mathematical ProgrammingNumerical AnalysisNonlinear ControlOptimal ControlEngineering	2008	1.1K
Evolution Strategies as a Scalable Alternative to Reinforcement Learning Tim Salimans, Jonathan Ho, Xi Chen arXiv (Cornell University) Artificial IntelligencePolicy GradientsEngineeringMachine LearningGame Theory	2017	1K
Reinforcement Learning in Continuous Time and Space Kenji Doya Neural Computation Artificial IntelligenceEngineeringMachine LearningValue Function ApproximationPriori Discretization	2000	978
On the Convergence of Stochastic Iterative Dynamic Programming Algorithms Tommi Jaakkola, Michael I. Jordan, Satinder Singh Neural Computation Mathematical ProgrammingArtificial IntelligenceEngineeringMachine LearningValue Function Approximation	1994	794
Regression methods for pricing complex American-style options John N. Tsitsiklis, Benjamin Van Roy IEEE Transactions on Neural Networks Mathematical ProgrammingOption PricingRepresentative StatesEngineeringValue Function	2001	637

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