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Reinforcement Learning (RL)

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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/blliu6/appirl

공식 코드

Automated Proof of Polynomial Inequalities via Reinforcement Learning

https://github.com/blrsai/release_tp_competition_code

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Pac-Man Pete: An extensible framework for building AI in VEX Robotics

https://github.com/blrsai/vexai-sim

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Pac-Man Pete: An extensible framework for building AI in VEX Robotics

https://github.com/bluddy/lean_rl

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Robotic Surgery With Lean Reinforcement Learning

https://github.com/bluecontra/AAAI2021-VDFP

공식 코드

Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction

https://github.com/bluecontra/CHAIN

공식 코드

Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn

https://github.com/bluewoods127/db-2025

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Diffusion Blend: Inference-Time Multi-Preference Alignment for Diffusion Models

https://github.com/blyucs/autogmap

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AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars

https://github.com/bmanczak/runPowerNetworks

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Hierarchical Reinforcement Learning for Power Network Topology Control

https://github.com/bmazoure/ctrl_public

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Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL

https://github.com/bmazoure/sparseMuJoCo

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Leveraging exploration in off-policy algorithms via normalizing flows

https://github.com/bnn-upc/drl-es-otn

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Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies

https://github.com/bo-pang/olsbpi

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Reinforcement Learning for Adaptive Optimal Stationary Control of Linear Stochastic Systems

https://github.com/boettiger-lab/rl-intro

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Deep Reinforcement Learning for Conservation Decisions

https://github.com/boettiger-lab/rl4fisheries

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Using machine learning to inform harvest control rule design in complex fishery settings

https://github.com/borealisai/sasrec-ccql

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Robust Reinforcement Learning Objectives for Sequential Recommender Systems

https://github.com/borgr/DORA

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DORA The Explorer: Directed Outreaching Reinforcement Action-Selection

https://github.com/boschresearch/DD_OPG

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Trajectory-Based Off-Policy Deep Reinforcement Learning

https://github.com/boschresearch/trust-region-layers

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Differentiable Trust Region Layers for Deep Reinforcement Learning

https://github.com/boschresearch/ube-mbrl

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Model-Based Uncertainty in Value Functions

https://github.com/bossdm/importancesampling

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Low Variance Off-policy Evaluation with State-based Importance Sampling

https://github.com/bowang-lab/ctrl-dna

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Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RL

https://github.com/brachiation-rl/brachiation

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Learning to Brachiate via Simplified Model Imitation

https://github.com/braemt/attentive-multi-task-deep-reinforcement-learning

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Attentive Multi-Task Deep Reinforcement Learning

https://github.com/brain-machine-intelligence/simul-mdps

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On the Reliability and Generalizability of Brain-inspired Reinforcement Learning Algorithms

https://github.com/brain-research/batch-ppo

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TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow

https://github.com/bramgrooten/automatic-noise-filtering

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Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning

https://github.com/bramgrooten/deeprl-for-hanabi

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Is Vanilla Policy Gradient Overlooked? Analyzing Deep Reinforcement Learning for Hanabi

https://github.com/brett-daley/fast-dqn

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Human-Level Control without Server-Grade Hardware

https://github.com/brett-daley/trajectory-aware-etraces

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Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning

https://github.com/brett-daley/virtual-replay-cache

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Virtual Replay Cache

https://github.com/brucegeli/tce_rl

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Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning

https://github.com/bruceyg/dpo-mbr

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Direct Preference Optimization for Neural Machine Translation with Minimum Bayes Risk Decoding

https://github.com/bryanoliveira/sliding-puzzles-gym

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Sliding Puzzles Gym: A Scalable Benchmark for State Representation in Visual Reinforcement Learning

https://github.com/bsen/performative-rl-gradually-shifting-envs

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Performative Reinforcement Learning in Gradually Shifting Environments

https://github.com/bstadie/third_person_im

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Third-Person Imitation Learning

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