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 3301–3350 of 15113 papers

TitleStatusHype
Agent Modeling as Auxiliary Task for Deep Reinforcement Learning—0
Decentralized Deep Reinforcement Learning for Network Level Traffic Signal Control—0
A SUMO Framework for Deep Reinforcement Learning Experiments Solving Electric Vehicle Charging Dispatching Problem—0
Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems—0
Decentralized Federated Reinforcement Learning for User-Centric Dynamic TFDD Control—0
Decentralized Global Connectivity Maintenance for Multi-Robot Navigation: A Reinforcement Learning Approach—0
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks—0
Decentralized Graph-Based Multi-Agent Reinforcement Learning Using Reward Machines—0
Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations—0
Decentralized model-free reinforcement learning in stochastic games with average-reward objective—0
A Review of Deep Reinforcement Learning for Smart Building Energy Management—0
A Succinct Summary of Reinforcement Learning—0
Deep Reinforcement Learning for Simultaneous Sensing and Channel Access in Cognitive Networks—0
Decentralized Multi-Agent Reinforcement Learning for Task Offloading Under Uncertainty—0
Decentralized Multi-Agent Reinforcement Learning: An Off-Policy Method—0
Decentralized Multi-Robot Formation Control Using Reinforcement Learning—0
Decentralized Reinforcement Learning for Multi-Target Search and Detection by a Team of Drones—0
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions—0
A Gentle Lecture Note on Filtrations in Reinforcement Learning—0
Decentralized Safe Reinforcement Learning for Voltage Control—0
A Subgame Perfect Equilibrium Reinforcement Learning Approach to Time-inconsistent Problems—0
Decentralized Semantic Traffic Control in AVs Using RL and DQN for Dynamic Roadblocks—0
AdaMemento: Adaptive Memory-Assisted Policy Optimization for Reinforcement Learning—0
Nearest-Neighbor-based Collision Avoidance for Quadrotors via Reinforcement Learning—0
Attention-Aware Face Hallucination via Deep Reinforcement Learning—0
Decentralizing Multi-Agent Reinforcement Learning with Temporal Causal Information—0
Deception in Social Learning: A Multi-Agent Reinforcement Learning Perspective—0
Deep Reinforcement Learning for Single-Shot Diagnosis and Adaptation in Damaged Robots—0
Deceptive Reinforcement Learning for Privacy-Preserving Planning—0
Deceptive Reinforcement Learning in Model-Free Domains—0
Deep Reinforcement Learning for Smart Home Energy Management—0
CQM: Curriculum Reinforcement Learning with a Quantized World Model—0
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning—0
Attention-based Fault-tolerant Approach for Multi-agent Reinforcement Learning Systems—0
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making—0
Decision-making at Unsignalized Intersection for Autonomous Vehicles: Left-turn Maneuver with Deep Reinforcement Learning—0
Decision-making for Autonomous Vehicles on Highway: Deep Reinforcement Learning with Continuous Action Horizon—0
Decision Making in Non-Stationary Environments with Policy-Augmented Monte Carlo Tree Search—0
Decision-making Strategy on Highway for Autonomous Vehicles using Deep Reinforcement Learning—0
Attention-driven Robotic Manipulation—0
Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling—0
Decision SpikeFormer: Spike-Driven Transformer for Decision Making—0
Decision Transformer for IRS-Assisted Systems with Diffusion-Driven Generative Channels—0
AgentGraph: Towards Universal Dialogue Management with Structured Deep Reinforcement Learning—0
Decision Transformers for RIS-Assisted Systems with Diffusion Model-Based Channel Acquisition—0
Decoding Molecular Graph Embeddings with Reinforcement Learning—0
Decoding Polar Codes with Reinforcement Learning—0
Decoding surface codes with deep reinforcement learning and probabilistic policy reuse—0
Attention Routing: track-assignment detailed routing using attention-based reinforcement learning—0
CPL: Critical Plan Step Learning Boosts LLM Generalization in Reasoning Tasks—0
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Benchmark Results

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