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 9251–9300 of 15113 papers

TitleStatusHype
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection—0
Reinforcement Learning in Low-Rank MDPs with Density Features—0
Reinforcement Learning for Economic Policy: A New Frontier?—0
Reinforcement Learning in Medical Image Analysis: Concepts, Applications, Challenges, and Future Directions—0
Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions—0
Reinforcement Learning in Multi-Party Trading Dialog—0
Reinforcement Learning in Newcomblike Environments—0
Reinforcement Learning in Non-Markovian Environments—0
Reinforcement Learning in Non-Markov Market-Making—0
Reinforcement Learning in Non-Stationary Environments—0
Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games—0
Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets—0
Reinforcement Learning in Presence of Discrete Markovian Context Evolution—0
Reinforcement Learning in R—0
Reinforcement Learning in Reward-Mixing MDPs—0
Reinforcement Learning in Rich-Observation MDPs using Spectral Methods—0
Reinforcement Learning in Robotic Motion Planning by Combined Experience-based Planning and Self-Imitation Learning—0
Reinforcement Learning in Robust Markov Decision Processes—0
Reinforcement Learning in Strategy-Based and Atari Games: A Review of Google DeepMinds Innovations—0
Reinforcement Learning in System Identification—0
Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplace—0
Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer—0
Demystifying Reinforcement Learning in Time-Varying Systems—0
Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation—0
Reinforcement Learning Methods for Wordle: A POMDP/Adaptive Control Approach—0
Reinforcement Learning Models of Human Behavior: Reward Processing in Mental Disorders—0
Reinforcement Learning of Cooperative Persuasive Dialogue Policies using Framing—0
Reinforcement Learning of Graph Neural Networks for Service Function Chaining—0
Reinforcement Learning of Implicit and Explicit Control Flow in Instructions—0
Reinforcement Learning of Markov Decision Processes with Peak Constraints—0
Reinforcement learning of minimalist grammars—0
Reinforcement Learning of Minimalist Numeral Grammars—0
Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings—0
Reinforcement Learning of Multi-Issue Negotiation Dialogue Policies—0
Reinforcement learning of optimal active particle navigation—0
Reinforcement Learning of POMDPs using Spectral Methods—0
Reinforcement Learning of Question-Answering Dialogue Policies for Virtual Museum Guides—0
Reinforcement learning of rare diffusive dynamics—0
Reinforcement Learning of Sequential Price Mechanisms—0
Reinforcement Learning of Speech Recognition System Based on Policy Gradient and Hypothesis Selection—0
Reinforcement Learning of Structured Control for Linear Systems with Unknown State Matrix—0
Reinforcement Learning of Theorem Proving—0
Reinforcement Learning of the Prediction Horizon in Model Predictive Control—0
Reinforcement Learning of Two-Issue Negotiation Dialogue Policies—0
Reinforcement Learning on Computational Resource Allocation of Cloud-based Wireless Networks—0
Reinforcement Learning on Encrypted Data—0
Graph neural networks-based Scheduler for Production planning problems using Reinforcement Learning—0
Reinforcement Learning Policy Recommendation for Interbank Network Stability—0
Reinforcement-Learning Portfolio Allocation with Dynamic Embedding of Market Information—0
Reinforcement Learning Portfolio Manager Framework with Monte Carlo Simulation—0
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Benchmark Results

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