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 42014250 of 15113 papers

TitleStatusHype
Adaptive patch foraging in deep reinforcement learning agents0
Adaptive perturbation adversarial training: based on reinforcement learning0
Adaptive Policy Learning for Offline-to-Online Reinforcement Learning0
Adaptive Policy Transfer in Reinforcement Learning0
Adaptive Probabilistic Trajectory Optimization via Efficient Approximate Inference0
Adaptive Q-learning for Interaction-Limited Reinforcement Learning0
Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning0
Adaptive Reinforcement Learning for Unobservable Random Delays0
Adaptive Reinforcement Learning for State Avoidance in Discrete Event Systems0
Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises0
Adaptive Reinforcement Learning through Evolving Self-Modifying Neural Networks0
Adaptive Reward-Poisoning Attacks against Reinforcement Learning0
Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions using Reinforcement Learning0
Adaptive Rollout Length for Model-Based RL Using Model-Free Deep RL0
Adaptive routing protocols for determining optimal paths in AI multi-agent systems: a priority- and learning-enhanced approach0
Adaptive Safe Reinforcement Learning-Enabled Optimization of Battery Fast-Charging Protocols0
Adaptive Sampling Quasi-Newton Methods for Derivative-Free Stochastic Optimization0
Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization0
Adaptive Security Policy Management in Cloud Environments Using Reinforcement Learning0
Adaptive Selection of Informative Path Planning Strategies via Reinforcement Learning0
Adaptive Shooting for Bots in First Person Shooter Games Using Reinforcement Learning0
Adaptive Stochastic ADMM for Decentralized Reinforcement Learning in Edge Industrial IoT0
Adaptive Stochastic Nonlinear Model Predictive Control with Look-ahead Deep Reinforcement Learning for Autonomous Vehicle Motion Control0
Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning0
Adaptive Stress Testing for Adversarial Learning in a Financial Environment0
Adaptive Stress Testing for Autonomous Vehicles0
Adaptive Stress Testing without Domain Heuristics using Go-Explore0
Adaptive Structural Hyper-Parameter Configuration by Q-Learning0
Adaptive Temporal Difference Learning with Linear Function Approximation0
Adaptive Torque Control of Exoskeletons under Spasticity Conditions via Reinforcement Learning0
Adaptive Trade-Offs in Off-Policy Learning0
Adaptive trading strategies across liquidity pools0
Reinforcement Learning for Adaptive Traffic Signal Control: Turn-Based and Time-Based Approaches to Reduce Congestion0
Adaptive Transit Signal Priority based on Deep Reinforcement Learning and Connected Vehicles in a Traffic Microsimulation Environment0
Adaptive Tree Backup Algorithms for Temporal-Difference Reinforcement Learning0
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs0
Adaptive User Journeys in Pharma E-Commerce with Reinforcement Learning: Insights from SwipeRx0
Adaptive Warm-Start MCTS in AlphaZero-like Deep Reinforcement Learning0
Adapt-to-Learn: Policy Transfer in Reinforcement Learning0
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems0
A Database of Multimodal Data to Construct a Simulated Dialogue Partner with Varying Degrees of Cognitive Health0
A data-driven choice of misfit function for FWI using reinforcement learning0
A Data-Driven Model-Reference Adaptive Control Approach Based on Reinforcement Learning0
A Dataset for Developing and Benchmarking Active Vision0
AdaTest:Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection0
AdaWM: Adaptive World Model based Planning for Autonomous Driving0
Adding Conditional Control to Diffusion Models with Reinforcement Learning0
Addressing Distribution Shift in Online Reinforcement Learning with Offline Datasets0
Addressing Extrapolation Error in Deep Offline Reinforcement Learning0
Addressing Inherent Uncertainty: Risk-Sensitive Behavior Generation for Automated Driving using Distributional Reinforcement Learning0
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Benchmark Results

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