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Reinforcement Learning (RL)

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하위 태스크: 6
평가표: 2
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/nohtow/wtf-rl

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Distinctive Image Captioning: Leveraging Ground Truth Captions in CLIP Guided Reinforcement Learning

https://github.com/nokpil/SocialNet

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Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning

https://github.com/nolanwagener/safe_rl

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Safe Reinforcement Learning Using Advantage-Based Intervention

https://github.com/nortem/sitp

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Reinforcement Learning with Success Induced Task Prioritization

https://github.com/npaulinastevia/drl_se

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A Comparison of Reinforcement Learning Frameworks for Software Testing Tasks

https://github.com/nrel/powergridworld

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PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems

https://github.com/nrel/rlc4clr

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Curriculum-based Reinforcement Learning for Distribution System Critical Load Restoration

https://github.com/nrontsis/PILCO

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SafePILCO: a software tool for safe and data-efficient policy synthesis

https://github.com/nsaph-projects/weather2alert

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Optimizing Heat Alert Issuance with Reinforcement Learning

https://github.com/nsidn98/NICE

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NICE: Robust Scheduling through Reinforcement Learning-Guided Integer Programming

https://github.com/nsidn98/informarl

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Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation

https://github.com/ntienvu/BOIL

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Bayesian Optimization for Iterative Learning

https://github.com/ntnghia1908/master_thesis

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Reinforcement Learning -based Adaptation and Scheduling Methods for Multi-source DASH

https://github.com/ntt-dkiku/evrp-eps

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Electric Vehicle Routing Problem for Emergency Power Supply: Towards Telecom Base Station Relief

https://github.com/nu-dialogue/antor

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Adaptive Natural Language Generation for Task-oriented Dialogue via Reinforcement Learning

https://github.com/nu-dialogue/post-processing-networks

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Post-processing Networks: Method for Optimizing Pipeline Task-oriented Dialogue Systems using Reinforcement Learning

https://github.com/nubot-nudt/SG-D3QN

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Robot Navigation in a Crowd by Integrating Deep Reinforcement Learning and Online Planning

https://github.com/nuria95/O-RAAC

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Risk-Averse Offline Reinforcement Learning

https://github.com/nusnlp/fspo

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The Hallucination Dilemma: Factuality-Aware Reinforcement Learning for Large Reasoning Models

https://github.com/nvidia-cosmos/cosmos-reason1

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Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning

https://github.com/nvlabs/gbrl

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Gradient Boosting Reinforcement Learning

https://github.com/nvlabs/gbrl_sb3

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Gradient Boosting Reinforcement Learning

https://github.com/nvlabs/rlcc

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Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs

https://github.com/nycu-rl-bandits-lab/apg

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Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning

https://github.com/nyu-dl/QueryReformulator

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Task-Oriented Query Reformulation with Reinforcement Learning

https://github.com/nyu-dl/dl4mt-cdec

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Plan, Attend, Generate: Planning for Sequence-to-Sequence Models

https://github.com/nyu-larx/attack_metarl

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Sampling Attacks on Meta Reinforcement Learning: A Minimax Formulation and Complexity Analysis

https://github.com/oezyurty/exrec

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Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing

https://github.com/offdynamicsrl/off-dynamics-rl

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ODRL: A Benchmark for Off-Dynamics Reinforcement Learning

https://github.com/offworld-projects/research-halgan

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Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs

https://github.com/oist-cnru/ReMASTER

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Self-organization of action hierarchy and compositionality by reinforcement learning with recurrent neural networks

https://github.com/oist-cnru/Variational-Recurrent-Models

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Variational Recurrent Models for Solving Partially Observable Control Tasks

https://github.com/olivierjeunen/ndcg-disagreement

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On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-$n$ Recommendation

https://github.com/om-ai-lab/vlm-r1

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VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

https://github.com/omarathon/rl-multi-agent-car-parking

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Multi-Agent Car Parking using Reinforcement Learning

https://github.com/omardelarosa/pcgrl-brush

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Mixed-Initiative Level Design with RL Brush

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