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 66016650 of 15113 papers

TitleStatusHype
Functional Optimization Reinforcement Learning for Real-Time Bidding0
Guided Exploration in Reinforcement Learning via Monte Carlo Critic OptimizationCode0
Hierarchical Reinforcement Learning with Opponent Modeling for Distributed Multi-agent Cooperation0
Dynamic network congestion pricing based on deep reinforcement learning0
Learning the policy for mixed electric platoon control of automated and human-driven vehicles at signalized intersection: a random search approach0
Joint Representation Training in Sequential Tasks with Shared Structure0
Eco-driving for Electric Connected Vehicles at Signalized Intersections: A Parameterized Reinforcement Learning approach0
Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning0
Reinforcement learning based adaptive metaheuristicsCode0
Modeling Adaptive Platoon and Reservation Based Autonomous Intersection Control: A Deep Reinforcement Learning Approach0
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems0
Value Function Decomposition for Iterative Design of Reinforcement Learning Agents0
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation0
The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality0
Reinforcement Learning under Partial Observability Guided by Learned Environment Models0
Recursive Reinforcement Learning0
A Federated Reinforcement Learning Method with Quantization for Cooperative Edge Caching in Fog Radio Access Networks0
Learning Agile Skills via Adversarial Imitation of Rough Partial Demonstrations0
CGAR: Critic Guided Action Redistribution in Reinforcement LeaningCode0
Learning Optimal Treatment Strategies for Sepsis Using Offline Reinforcement Learning in Continuous Space0
Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation0
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks0
Fusion of Model-free Reinforcement Learning with Microgrid Control: Review and Vision0
Multi-Horizon Representations with Hierarchical Forward Models for Reinforcement LearningCode0
Auto-Encoding Adversarial Imitation Learning0
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy TransferCode0
Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data0
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement LearningCode0
Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation ApproachCode0
Model-Based Imitation Learning Using Entropy Regularization of Model and Policy0
The Integration of Machine Learning into Automated Test Generation: A Systematic Mapping Study0
Safe and Psychologically Pleasant Traffic Signal Control with Reinforcement Learning using Action Masking0
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL0
Hybridization of evolutionary algorithm and deep reinforcement learning for multi-objective orienteering optimization0
Federated Stochastic Approximation under Markov Noise and Heterogeneity: Applications in Reinforcement Learning0
A Single-Timescale Analysis For Stochastic Approximation With Multiple Coupled Sequences0
Finding Optimal Policy for Queueing Models: New Parameterization0
Imitate then Transcend: Multi-Agent Optimal Execution with Dual-Window Denoise PPO0
Incorporating Voice Instructions in Model-Based Reinforcement Learning for Self-Driving Cars0
Guided Safe Shooting: model based reinforcement learning with safety constraints0
Deep reinforced active learning for multi-class image classification0
From Multi-agent to Multi-robot: A Scalable Training and Evaluation Platform for Multi-robot Reinforcement Learning0
Constrained Reinforcement Learning for Robotics via Scenario-Based Programming0
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?0
Two-Hop Age of Information Scheduling for Multi-UAV Assisted Mobile Edge Computing: FRL vs MADDPG0
A Survey on Model-based Reinforcement Learning0
Learning Multi-Task Transferable Rewards via Variational Inverse Reinforcement Learning0
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation0
Bootstrapped Transformer for Offline Reinforcement Learning0
Deep reinforcement learning for fMRI prediction of Autism Spectrum Disorder0
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Benchmark Results

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