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Showing 351–400 of 677 papers

TitleStatusHype
DropoutDAgger: A Bayesian Approach to Safe Imitation Learning—0
Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization—0
Effects of sparse rewards of different magnitudes in the speed of learning of model-based actor critic methods—0
Efficient Diversity-based Experience Replay for Deep Reinforcement Learning—0
Efficiently Training On-Policy Actor-Critic Networks in Robotic Deep Reinforcement Learning with Demonstration-like Sampled Exploration—0
Mind's Eye: Grounded Language Model Reasoning through Simulation—0
Model-based Adversarial Imitation Learning—0
Model-Based Reward Shaping for Adversarial Inverse Reinforcement Learning in Stochastic Environments—0
Model-Invariant State Abstractions for Model-Based Reinforcement Learning—0
MQES: Max-Q Entropy Search for Efficient Exploration in Continuous Reinforcement Learning—0
Multi-Object Grasping in the Plane—0
Multi-Objective Algorithms for Learning Open-Ended Robotic Problems—0
Multi-Path Policy Optimization—0
Multi-step Greedy Reinforcement Learning Algorithms—0
Multi-task Reinforcement Learning with a Planning Quasi-Metric—0
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning—0
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning—0
Neural Episodic Control with State Abstraction—0
Neural Population Learning beyond Symmetric Zero-sum Games—0
Neuroplastic Expansion in Deep Reinforcement Learning—0
Non-local Policy Optimization via Diversity-regularized Collaborative Exploration—0
OER: Offline Experience Replay for Continual Offline Reinforcement Learning—0
Offline Imitation Learning with a Misspecified Simulator—0
Offline Multi-agent Reinforcement Learning via Score Decomposition—0
Offline Robot Reinforcement Learning with Uncertainty-Guided Human Expert Sampling—0
Off-OAB: Off-Policy Policy Gradient Method with Optimal Action-Dependent Baseline—0
Off-Policy Deep Reinforcement Learning Algorithms for Handling Various Robotic Manipulator Tasks—0
One is More: Diverse Perspectives within a Single Network for Efficient DRL—0
On-Policy Model Errors in Reinforcement Learning—0
On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling—0
On Proximal Policy Optimization's Heavy-tailed Gradients—0
On Representation Complexity of Model-based and Model-free Reinforcement Learning—0
On the Convergence Theory of Meta Reinforcement Learning with Personalized Policies—0
On the Geometry of Reinforcement Learning in Continuous State and Action Spaces—0
OPAC: Opportunistic Actor-Critic—0
OVD-Explorer: A General Information-theoretic Exploration Approach for Reinforcement Learning—0
OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments—0
Overcoming Model Bias for Robust Offline Deep Reinforcement Learning—0
Parareal with a Learned Coarse Model for Robotic Manipulation—0
Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning—0
PGPS : Coupling Policy Gradient with Population-based Search—0
Phasic Diversity Optimization for Population-Based Reinforcement Learning—0
Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning—0
Policy Gradient with Kernel Quadrature—0
Policy Gradient With Serial Markov Chain Reasoning—0
Policy Optimization by Genetic Distillation—0
Certifiably Robust Reinforcement Learning through Model-Based Abstract Interpretation—0
Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space—0
Policy Search by Target Distribution Learning for Continuous Control—0
Policy Search using Dynamic Mirror Descent MPC for Model Free Off Policy RL—0
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