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

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Showing 5001–5025 of 15113 papers

TitleStatusHype
Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning—0
Evolutionary Quantum Architecture Search for Parametrized Quantum Circuits—0
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning—0
GenTUS: Simulating User Behaviour and Language in Task-oriented Dialogues with Generative Transformers—0
An intelligent algorithmic trading based on a risk-return reinforcement learning algorithm—0
Solving Royal Game of Ur Using Reinforcement LearningCode0
What deep reinforcement learning tells us about human motor learning and vice-versa—0
Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics—0
Quantum Multi-Agent Meta Reinforcement Learning—0
Improving Sample Efficiency in Evolutionary RL Using Off-Policy Ranking—0
BARReL: Bottleneck Attention for Adversarial Robustness in Vision-Based Reinforcement Learning—0
Incorporating Rivalry in Reinforcement Learning for a Competitive GameCode0
Weighted Maximum Entropy Inverse Reinforcement Learning—0
Spectral Decomposition Representation for Reinforcement Learning—0
Unified Policy Optimization for Continuous-action Reinforcement Learning in Non-stationary Tasks and Games—0
Entropy Augmented Reinforcement Learning—0
Improving Post-Processing of Audio Event Detectors Using Reinforcement LearningCode0
MARTI-4: new model of human brain, considering neocortex and basal ganglia -- learns to play Atari game by reinforcement learning on a single CPU—0
A Review of Uncertainty for Deep Reinforcement Learning—0
Hybrid Learning with New Value Function for the Maximum Common Subgraph Problem—0
Explainable Reinforcement Learning on Financial Stock Trading using SHAP—0
Intelligent problem-solving as integrated hierarchical reinforcement learning—0
Choquet regularization for reinforcement learning—0
Autonomous Resource Management in Construction Companies Using Deep Reinforcement Learning Based on IoT—0
Performance Optimization for Semantic Communications: An Attention-based Reinforcement Learning Approach—0
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Benchmark Results

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