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 11451–11500 of 15113 papers

TitleStatusHype
Identifying Cognitive Radars -- Inverse Reinforcement Learning using Revealed Preferences—0
Adversary A3C for Robust Reinforcement Learning—0
Optimization for Reinforcement Learning: From Single Agent to Cooperative Agents—0
Regret Bounds for Learning State Representations in Reinforcement Learning—0
Propagating Uncertainty in Reinforcement Learning via Wasserstein BarycentersCode0
Privacy-Preserving Q-Learning with Functional Noise in Continuous SpacesCode0
No-Press Diplomacy: Modeling Multi-Agent Gameplay—0
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle—0
SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional PoliciesCode0
Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement LearningCode0
Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes—0
Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning—0
Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy—0
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement LearningCode0
Neural Temporal-Difference Learning Converges to Global Optima—0
Learning Generalizable Device Placement Algorithms for Distributed Machine LearningCode0
A Model-Based Reinforcement Learning with Adversarial Training for Online RecommendationCode0
A Family of Robust Stochastic Operators for Reinforcement Learning—0
Learning Local Search Heuristics for Boolean SatisfiabilityCode0
Explicit Planning for Efficient Exploration in Reinforcement Learning—0
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement LearningCode1
Learning Reward Machines for Partially Observable Reinforcement LearningCode0
Adaptive Auxiliary Task Weighting for Reinforcement LearningCode0
Park: An Open Platform for Learning-Augmented Computer SystemsCode0
Regret Minimization for Reinforcement Learning with Vectorial Feedback and Complex ObjectivesCode0
Staying up to Date with Online Content Changes Using Reinforcement Learning for SchedulingCode1
Mix and Match: Markov Chains & Mixing Times for Matching in Rideshare—0
IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks—0
Quadratic Q-network for Learning Continuous Control for Autonomous Vehicles—0
Simulation-based reinforcement learning for real-world autonomous drivingCode0
Induction of Subgoal Automata for Reinforcement Learning—0
Distributed Soft Actor-Critic with Multivariate Reward Representation and Knowledge DistillationCode0
Multi-Agent Deep Reinforcement Learning with Adaptive Policies—0
Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learningCode0
Stigmergic Independent Reinforcement Learning for Multi-Agent Collaboration—0
Augmented Random Search for Quadcopter Control: An alternative to Reinforcement Learning—0
Improving Neural Relation Extraction with Positive and Unlabeled Learning—0
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction—0
Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy OptimizationCode0
Restoring Chaos Using Deep Reinforcement Learning—0
Towards Similarity Graphs Constructed by Deep Reinforcement LearningCode0
Improving Fictitious Play Reinforcement Learning with Expanding Models—0
GRIm-RePR: Prioritising Generating Important Features for Pseudo-Rehearsal—0
Adversarial Deep Reinforcement Learning based Adaptive Moving Target Defense—0
Behavior Regularized Offline Reinforcement Learning—0
A General Framework on Enhancing Portfolio Management with Reinforcement Learning—0
Join Query Optimization with Deep Reinforcement Learning AlgorithmsCode0
Control-Tutored Reinforcement Learning: an application to the Herding Problem—0
Natural Language Generation Using Reinforcement Learning with External RewardsCode0
Multi-Vehicle Mixed-Reality Reinforcement Learning for Autonomous Multi-Lane Driving—0
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Benchmark Results

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