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Policy Gradient Methods

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Showing 301–350 of 382 papers

TitleStatusHype
Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable ModelsCode0
Fast Efficient Hyperparameter Tuning for Policy GradientsCode0
Diverse Exploration via Conjugate Policies for Policy Gradient Methods—0
On-Policy Trust Region Policy Optimisation with Replay BuffersCode0
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning—0
AdaFrame: Adaptive Frame Selection for Fast Video Recognition—0
An Off-policy Policy Gradient Theorem Using Emphatic Weightings—0
Reward-estimation variance elimination in sequential decision processes—0
Bayesian Action Decoder for Deep Multi-Agent Reinforcement LearningCode1
Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy ImprovementCode0
Risk-Sensitive Reinforcement Learning via Policy Gradient Search—0
Policy Gradient in Partially Observable Environments: Approximation and Convergence—0
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient MethodsCode0
CaLcs: Continuously Approximating Longest Common Subsequence for Sequence Level Optimization—0
Training for Diversity in Image Paragraph CaptioningCode0
Countering Language Drift via Grounding—0
Assumption Questioning: Latent Copying and Reward Exploitation in Question Generation—0
The wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions—0
Improvements on Hindsight Learning—0
Image Captioning based on Deep Reinforcement Learning—0
Learning to Interrupt: A Hierarchical Deep Reinforcement Learning Framework for Efficient Exploration—0
Remember and Forget for Experience ReplayCode0
Variance Reduction for Reinforcement Learning in Input-Driven Environments—0
Learning Goal-Oriented Visual Dialog via Tempered Policy GradientCode0
Policy Optimization with Demonstrations—0
Focused Hierarchical RNNs for Conditional Sequence Processing—0
Fingerprint Policy Optimisation for Robust Reinforcement Learning—0
Learning Self-Imitating Diverse Policies—0
Multiagent Soft Q-Learning—0
On Learning Intrinsic Rewards for Policy Gradient MethodsCode0
Information Maximizing Exploration with a Latent Dynamics Model—0
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines—0
The Mirage of Action-Dependent Baselines in Reinforcement LearningCode0
Optimizing over a Restricted Policy Class in Markov Decision Processes—0
Asynchronous stochastic approximations with asymptotically biased errors and deep multi-agent learning—0
Clipped Action Policy GradientCode0
Policy Gradients for Contextual Recommendations—0
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator—0
Expected Policy Gradients for Reinforcement Learning—0
Global Convergence of Policy Gradient Methods for Linearized Control Problems—0
Predicting Multiple Actions for Stochastic Continuous Control—0
Adversarial Policy Gradient for Alternating Markov Games—0
Action-dependent Control Variates for Policy Optimization via Stein Identity—0
Understanding Grounded Language Learning Agents—0
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking AgentsCode0
Bayesian Policy Gradients via Alpha Divergence Dropout InferenceCode0
Adaptive Batch Size for Safe Policy Gradients—0
Divide-and-Conquer Reinforcement LearningCode0
Run, skeleton, run: skeletal model in a physics-based simulationCode0
Hindsight policy gradientsCode0
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