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Deep RL

3,861 papers

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Papers

Addressing Action Oscillations through Learning Policy Inertia AAAI 2021
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning AAAI 2021
Reinforcement Learning with Trajectory Feedback AAAI 2021
Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning AAAI 2021
Stabilizing Q Learning Via Soft Mellowmax Operator AAAI 2021
DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning AAAI 2021
Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs AAAI 2021
Reinforcement Learning Based Multi-Agent Resilient Control: From Deep Neural Networks to an Adaptive Law AAAI 2021
Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning AAAI 2021
Variance Penalized On-Policy and Off-Policy Actor-Critic AAAI 2021
Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks AAAI 2021
Metrics and Continuity in Reinforcement Learning AAAI 2021
Bayesian Distributional Policy Gradients AAAI 2021
Distributional Reinforcement Learning via Moment Matching AAAI 2021
Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach AAAI 2021
Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation AAAI 2021
Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks AAAI 2021
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction AAAI 2021
Expected Eligibility Traces AAAI 2021
Self-Supervised Attention-Aware Reinforcement Learning AAAI 2021
Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling AAAI 2021
Robust Bandit Learning with Imperfect Context AAAI 2021
On Convergence of Gradient Expected Sarsa(λ) AAAI 2021
WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning AAAI 2021
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images AAAI 2021