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

Showing 59516000 of 15113 papers

TitleStatusHype
An Intelligent End-to-End Neural Architecture Search Framework for Electricity Forecasting Model Development0
Dealing with Sparse Rewards Using Graph Neural Networks0
Horizon-Free Reinforcement Learning in Polynomial Time: the Power of Stationary Policies0
Deep reinforcement learning for optimal well control in subsurface systems with uncertain geology0
Bellman Residual Orthogonalization for Offline Reinforcement Learning0
MERLIN -- Malware Evasion with Reinforcement LearnINg0
Remember and Forget Experience Replay for Multi-Agent Reinforcement Learning0
Advanced Skills through Multiple Adversarial Motion Priors in Reinforcement Learning0
Asynchronous Reinforcement Learning for Real-Time Control of Physical RobotsCode1
An Optical Control Environment for Benchmarking Reinforcement Learning AlgorithmsCode0
Possibility Before Utility: Learning And Using Hierarchical AffordancesCode1
The state-of-the-art review on resource allocation problem using artificial intelligence methods on various computing paradigms0
NovGrid: A Flexible Grid World for Evaluating Agent Response to Novelty0
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games0
Review of Metrics to Measure the Stability, Robustness and Resilience of Reinforcement Learning0
Reinforcement-based frugal learning for satellite image change detection0
X-MEN: Guaranteed XOR-Maximum Entropy Constrained Inverse Reinforcement Learning0
A Primer on Maximum Causal Entropy Inverse Reinforcement Learning0
Is Vanilla Policy Gradient Overlooked? Analyzing Deep Reinforcement Learning for HanabiCode0
Insights From the NeurIPS 2021 NetHack ChallengeCode0
FrameHopper: Selective Processing of Video Frames in Detection-driven Real-Time Video Analytics0
Explainability in reinforcement learning: perspective and position0
Linear convergence of a policy gradient method for some finite horizon continuous time control problems0
ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement LearningCode0
Optimizing Trajectories for Highway Driving with Offline Reinforcement Learning0
Self-Imitation Learning from Demonstrations0
Long Short-Term Memory for Spatial Encoding in Multi-Agent Path PlanningCode0
Multitask Neuroevolution for Reinforcement Learning with Long and Short Episodes0
Perceiving the World: Question-guided Reinforcement Learning for Text-based GamesCode0
Entailment Relation Aware Paraphrase Generation0
Learning on the Job: Long-Term Behavioural Adaptation in Human-Robot Interactions0
Explicit User Manipulation in Reinforcement Learning Based Recommender Systems0
Hierarchical Reinforcement Learning of Locomotion Policies in Response to Approaching Objects: A Preliminary Study0
MicroRacer: a didactic environment for Deep Reinforcement LearningCode0
Reinforcement learning reward function in unmanned aerial vehicle control tasks0
Policy Gradients using Variational Quantum Circuits0
Model-based Multi-agent Reinforcement Learning: Recent Progress and Prospects0
Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit DesignCode1
Reinforcement learning for automatic quadrilateral mesh generation: a soft actor-critic approachCode1
Teachable Reinforcement Learning via Advice DistillationCode1
Thompson Sampling on Asymmetric α-Stable Bandits0
Risk-Sensitive Bayesian Games for Multi-Agent Reinforcement Learning under Policy Uncertainty0
Privacy-Preserving Reinforcement Learning Beyond Expectation0
Deep reinforcement learning guided graph neural networks for brain network analysis0
Infinite-Horizon Reach-Avoid Zero-Sum Games via Deep Reinforcement Learning0
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning0
Meta-Reinforcement Learning for the Tuning of PI Controllers: An Offline Approach0
Strategic Maneuver and Disruption with Reinforcement Learning Approaches for Multi-Agent Coordination0
GAC: A Deep Reinforcement Learning Model Toward User Incentivization in Unknown Social NetworksCode0
The Frost Hollow Experiments: Pavlovian Signalling as a Path to Coordination and Communication Between Agents0
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Benchmark Results

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