conftrace_

value function approximation

100 papers

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Also known as

VFA

Co-occurring keywords

reinforcement learning (4352) value function (295) markov decision process (790) policy iteration (99) off-policy learning (228) temporal difference learning (149) deep reinforcement learning (903) regret bound (1926) representation learning (6206) approximate dynamic programming (31)

Papers

Revisiting the Softmax Bellman Operator: New Benefits and New Perspective ICML 2019
A Family of Robust Stochastic Operators for Reinforcement Learning NIPS 2019
Representation Learning on Graphs: A Reinforcement Learning Application AISTATS 2019
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates NIPS 2019
Limiting Extrapolation in Linear Approximate Value Iteration NIPS 2019
Fully Parameterized Quantile Function for Distributional Reinforcement Learning NIPS 2019
Unsupervised Basis Function Adaptation for Reinforcement Learning JMLR 2019
Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces NIPS 2018
rho-POMDPs have Lipschitz-Continuous epsilon-Optimal Value Functions NIPS 2018
Beyond the One-Step Greedy Approach in Reinforcement Learning ICML 2018
Addressing Function Approximation Error in Actor-Critic Methods ICML 2018
Reward Estimation for Variance Reduction in Deep Reinforcement Learning CORL 2018
Scalable Bilinear Pi Learning Using State and Action Features ICML 2018
Natural Value Approximators: Learning when to Trust Past Estimates NIPS 2017
Policy Gradient With Value Function Approximation For Collective Multiagent Planning NIPS 2017
Count-Based Exploration in Feature Space for Reinforcement Learning IJCAI 2017
Shallow Updates for Deep Reinforcement Learning NIPS 2017
Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning ICML 2016
Linear Feature Encoding for Reinforcement Learning NIPS 2016
Hierarchical Decision Making In Electricity Grid Management ICML 2016
Basis refinement strategies for linear value function approximation in MDPs NIPS 2015
On the Rate of Convergence and Error Bounds for LSTD(λ) ICML 2015
Probabilistic Differential Dynamic Programming NIPS 2014
Off-policy Learning With Eligibility Traces: A Survey JMLR 2014
An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy ICML 2014