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 6451–6475 of 15113 papers

TitleStatusHype
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems—0
Benchmarking Deep Reinforcement Learning Algorithms for Vision-based Robotics—0
Active Reinforcement Learning -- A Roadmap Towards Curious Classifier Systems for Self-Adaptation—0
In Defense of the Unitary Scalarization for Deep Multi-Task LearningCode1
STIR^2: Reward Relabelling for combined Reinforcement and Imitation Learning on sparse-reward tasks—0
Pavlovian Signalling with General Value Functions in Agent-Agent Temporal Decision Making—0
Distributed Cooperative Multi-Agent Reinforcement Learning with Directed Coordination Graph—0
State of the Art of User Simulation approaches for conversational information retrieval—0
Opportunities of Hybrid Model-based Reinforcement Learning for Cell Therapy Manufacturing Process Control—0
When is Offline Two-Player Zero-Sum Markov Game Solvable?—0
Verified Probabilistic Policies for Deep Reinforcement LearningCode1
A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning—0
Assessing Policy, Loss and Planning Combinations in Reinforcement Learning using a New Modular Architecture—0
Mirror Learning: A Unifying Framework of Policy OptimisationCode1
Neural Network Optimization for Reinforcement Learning Tasks Using Sparse Computations—0
Offline Reinforcement Learning for Road Traffic Control—0
SABLAS: Learning Safe Control for Black-box Dynamical SystemsCode1
Combining Reinforcement Learning and Inverse Reinforcement Learning for Asset Allocation Recommendations—0
Sample Efficient Deep Reinforcement Learning via Uncertainty EstimationCode1
Offsetting Unequal Competition through RL-assisted Incentive Schemes—0
Using Simulation Optimization to Improve Zero-shot Policy Transfer of QuadrotorsCode1
Deep Reinforcement Learning, a textbook—0
Deep Learning-based Predictive Control of Battery Management for Frequency RegulationCode0
Learning Complex Spatial Behaviours in ABM: An Experimental Observational Study—0
Analyzing Micro-Founded General Equilibrium Models with Many Agents using Deep Reinforcement Learning—0
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Benchmark Results

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