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 8576–8600 of 15113 papers

TitleStatusHype
Multi-Objective Reinforcement Learning based Multi-Microgrid System Optimisation Problem—0
Using Cognitive Models to Train Warm Start Reinforcement Learning Agents for Human-Computer Interactions—0
Maximum Entropy RL (Provably) Solves Some Robust RL Problems—0
Streaming Linear System Identification with Reverse Experience Replay—0
WFA-IRL: Inverse Reinforcement Learning of Autonomous Behaviors Encoded as Weighted Finite Automata—0
A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems—0
Full Gradient DQN Reinforcement Learning: A Provably Convergent Scheme—0
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning—0
Learning to Explore a Class of Multiple Reward-Free Environments—0
Learning State Representations via Temporal Cycle-Consistency Constraint in Model-Based Reinforcement Learning—0
Less Suboptimal Learning and Control in Variational POMDPs—0
Learning Task Informed Abstractions—0
Automatic Goal Generation using Dynamical Distance Learning—0
Learning to Infer Unseen Contexts in Causal Contextual Reinforcement Learning—0
Pretraining Reward-Free Representations for Data-Efficient Reinforcement Learning—0
LOCO: Adaptive exploration in reinforcement learning via local estimation of contraction coefficients—0
Reinforcement Learning with Prototypical RepresentationsCode1
Solipsistic Reinforcement Learning—0
Out-of-distribution generalization of internal models is correlated with reward—0
Resolving Causal Confusion in Reinforcement Learning via Robust Exploration—0
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning—0
Minimum Description Length Skills for Accelerated Reinforcement Learning—0
The AI Arena: A Framework for Distributed Multi-Agent Reinforcement LearningCode1
Parametrized quantum policies for reinforcement learning—0
Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement LearningCode1
Show:102550
← PrevPage 344 of 605Next →

Benchmark Results

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