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 4601–4650 of 15113 papers

TitleStatusHype
Neural Packing: from Visual Sensing to Reinforcement Learning—0
Reinforcement learning with non-ergodic reward increments: robustness via ergodicity transformationsCode0
Reaching the Limit in Autonomous Racing: Optimal Control versus Reinforcement Learning—0
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning—0
Building Persona Consistent Dialogue Agents with Offline Reinforcement LearningCode0
Leveraging Topological Maps in Deep Reinforcement Learning for Multi-Object Navigation—0
Deep Reinforcement Learning with Explicit Context Representation—0
LgTS: Dynamic Task Sampling using LLM-generated sub-goals for Reinforcement Learning Agents—0
A Framework for Empowering Reinforcement Learning Agents with Causal Analysis: Enhancing Automated Cryptocurrency Trading—0
Hybrid Reinforcement Learning for Optimizing Pump Sustainability in Real-World Water Distribution Networks—0
Exploration with Principles for Diverse AI Supervision—0
Leveraging Optimal Transport for Enhanced Offline Reinforcement Learning in Surgical Robotic Environments—0
A Lightweight Calibrated Simulation Enabling Efficient Offline Learning for Optimal Control of Real BuildingsCode0
Learning RL-Policies for Joint Beamforming Without Exploration: A Batch Constrained Off-Policy ApproachCode0
Discerning Temporal Difference Learning—0
Novelty Detection in Reinforcement Learning with World Models—0
Dealing with uncertainty: balancing exploration and exploitation in deep recurrent reinforcement learningCode0
Virtual Augmented Reality for Atari Reinforcement LearningCode0
Reinforcement Learning-based Knowledge Graph Reasoning for Explainable Fact-checking—0
Off-Policy Evaluation for Human Feedback—0
Online RL in Linearly q^π-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore—0
Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization—0
Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning—0
Scalable Semantic Non-Markovian Simulation Proxy for Reinforcement Learning—0
Bi-Level Offline Policy Optimization with Limited Exploration—0
f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences—0
On Double Descent in Reinforcement Learning with LSTD and Random Features—0
When is Agnostic Reinforcement Learning Statistically Tractable?—0
Predictive auxiliary objectives in deep RL mimic learning in the brain—0
Multi-timestep models for Model-based Reinforcement Learning—0
Learning Generalizable Agents via Saliency-Guided Features Decorrelation—0
Distributional Reinforcement Learning with Online Risk-awareness Adaption—0
DeepQTest: Testing Autonomous Driving Systems with Reinforcement Learning and Real-world Weather DataCode0
Lifelong Learning for Fog Load Balancing: A Transfer Learning Approach—0
Optimal Sequential Decision-Making in Geosteering: A Reinforcement Learning Approach—0
Reinforced UI Instruction Grounding: Towards a Generic UI Task Automation API—0
Improving Offline-to-Online Reinforcement Learning with Q Conditioned State Entropy Exploration—0
Self-Confirming Transformer for Belief-Conditioned Adaptation in Offline Multi-Agent Reinforcement Learning—0
Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-Visual Environments: A Comparison—0
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems—0
How the level sampling process impacts zero-shot generalisation in deep reinforcement learning—0
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning—0
LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option FrameworkCode0
Resilient Legged Local Navigation: Learning to Traverse with Compromised Perception End-to-End—0
Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms—0
Optimal Control of District Cooling Energy Plant with Reinforcement Learning and MPC—0
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels—0
Neural architecture impact on identifying temporally extended Reinforcement Learning tasks—0
Proximal Policy Optimization-Based Reinforcement Learning Approach for DC-DC Boost Converter Control: A Comparative Evaluation Against Traditional Control Techniques—0
Searching for High-Value Molecules Using Reinforcement Learning and Transformers—0
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Benchmark Results

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