SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 12901–12950 of 15113 papers

TitleStatusHype
Augmented Memory Networks for Streaming-Based Active One-Shot Learning—0
Single-step Options for Adversary Driving—0
Optimizing thermodynamic trajectories using evolutionary and gradient-based reinforcement learningCode0
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context VariablesCode0
Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation—0
Hindsight Generative Adversarial Imitation Learning—0
Deep Reinforcement Learning with Decorrelation—0
Exploiting Hierarchy for Learning and Transfer in KL-regularized RL—0
A Comparison of Prediction Algorithms and Nexting for Short Term Weather Forecasts—0
Adaptive Genomic Evolution of Neural Network Topologies (AGENT) for State-to-Action Mapping in Autonomous Agents—0
Learning proposals for sequential importance samplers using reinforced variational inference—0
Robust Reinforcement Learning for Autonomous Driving—0
Multi-agent query reformulation: Challenges and the role of diversity—0
Policy Distillation and Value Matching in Multiagent Reinforcement Learning—0
Online Antenna Tuning in Heterogeneous Cellular Networks with Deep Reinforcement Learning—0
A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement LearningCode0
Deep Reinforcement Learning with Feedback-based ExplorationCode0
No-regret Exploration in Contextual Reinforcement Learning—0
Can User-Centered Reinforcement Learning Allow a Robot to Attract Passersby without Causing Discomfort?—0
gym-gazebo2, a toolkit for reinforcement learning using ROS 2 and GazeboCode0
Reinforcement Learning with Dynamic Boltzmann Softmax UpdatesCode0
On Applications of Bootstrap in Continuous Space Reinforcement Learning—0
ROS2Learn: a reinforcement learning framework for ROS 2Code0
Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems—0
VRKitchen: an Interactive 3D Virtual Environment for Task-oriented LearningCode0
Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning—0
Task-oriented Design through Deep Reinforcement Learning—0
CoaCor: Code Annotation for Code Retrieval with Reinforcement LearningCode0
Effective reinforcement learning based local search for the maximum k-plex problem—0
A Review of Reinforcement Learning for Autonomous Building Energy Management—0
Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces—0
Deep learning for molecular design - a review of the state of the art—0
Hybrid Reinforcement Learning with Expert State SequencesCode0
Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling—0
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy CriticsCode0
Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal ControlCode0
Orthogonal Estimation of Wasserstein Distances—0
Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks—0
Successive Over Relaxation Q-Learning—0
Adaptive Power System Emergency Control using Deep Reinforcement LearningCode0
DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning—0
Learning Self-Game-Play Agents for Combinatorial Optimization Problems—0
Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning—0
A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation—0
Learning Heuristics over Large Graphs via Deep Reinforcement LearningCode0
Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning—0
Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes—0
MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning ExperimentsCode0
Provably Robust Blackbox Optimization for Reinforcement Learning—0
RLOC: Neurobiologically Inspired Hierarchical Reinforcement Learning Algorithm for Continuous Control of Nonlinear Dynamical Systems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified