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Reinforcement Learning (RL)

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보존된 평가 기록: 3

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.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/citrineinformatics/multivariate-prediction-intervals

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Multivariate Prediction Intervals for Random Forests

https://github.com/cityflow-project/CityFlow

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CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

https://github.com/cityujun/hvac_offline_rl

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Experimental evaluation of offline reinforcement learning for HVAC control in buildings

https://github.com/cjdjr/t-maac

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Stabilizing Voltage in Power Distribution Networks via Multi-Agent Reinforcement Learning with Transformer

https://github.com/cjreinforce/jowa

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Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining

https://github.com/cjreinforce/pure

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Stop Summation: Min-Form Credit Assignment Is All Process Reward Model Needs for Reasoning

https://github.com/cjy1992/interp-e2e-driving

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Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning

https://github.com/ckorbach/nbv_rl

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Next-Best-View Estimation based on Deep Reinforcement Learning for Active Object Classification

https://github.com/ckrk/bidding_learning

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Computational Performance of Deep Reinforcement Learning to find Nash Equilibria

https://github.com/claire-labo/no-representation-no-trust

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No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO

https://github.com/clarkkev/deep-coref

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Deep Reinforcement Learning for Mention-Ranking Coreference Models

https://github.com/clearoboticslab/dclf-rl

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Decomposing Control Lyapunov Functions for Efficient Reinforcement Learning

https://github.com/clearoboticslab/tsymrl

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An Investigation of Time Reversal Symmetry in Reinforcement Learning

https://github.com/clementromac/lamorel

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Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning

https://github.com/clic-lab/blocks

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Mapping Instructions and Visual Observations to Actions with Reinforcement Learning

https://github.com/clinicalml/gumbel-max-scm

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Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models

https://github.com/clinicalml/trajectory-inspection

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Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies

https://github.com/clivesun01/nrsr

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Noise-Resilient Symbolic Regression with Dynamic Gating Reinforcement Learning

https://github.com/clmoro/robotics-rl-fms-integration

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Integrating Reinforcement Learning with Foundation Models for Autonomous Robotics: Methods and Perspectives

https://github.com/cloud-qu/lare

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Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning

https://github.com/clutr/clutr

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CLUTR: Curriculum Learning via Unsupervised Task Representation Learning

https://github.com/clvoloshin/COBS

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Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning

https://github.com/clvoloshin/OPE-tools

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Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning

https://github.com/clvrai/create

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Generalization to New Actions in Reinforcement Learning

https://github.com/clvrai/furniture-bench

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FurnitureBench: Reproducible Real-World Benchmark for Long-Horizon Complex Manipulation

https://github.com/clvrai/mopa-pd

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Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation

https://github.com/clvrai/new-actions-rl

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Generalization to New Actions in Reinforcement Learning

https://github.com/clvrai/spirl

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Accelerating Reinforcement Learning with Learned Skill Priors

https://github.com/cmu-safari/pythia

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Pythia: A Customizable Hardware Prefetching Framework Using Online Reinforcement Learning

https://github.com/cmudig/ai-clinician-mimiciv

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How Consistent are Clinicians? Evaluating the Predictability of Sepsis Disease Progression with Dynamics Models

https://github.com/coco0106/MO-STEP

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STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning

https://github.com/coco66/ttenv

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Learning to Track Dynamic Targets in Partially Known Environments

https://github.com/cog-isa/forger

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Forgetful Experience Replay in Hierarchical Reinforcement Learning from Demonstrations

https://github.com/cog-isa/schema-rl

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Delta Schema Network in Model-based Reinforcement Learning

https://github.com/cogneuroai/rl-with-scale-invariant-memory

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Deep reinforcement learning with time-scale invariant memory

https://github.com/cognizant-ai-labs/sepx-paper

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Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search

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