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Reinforcement Learning

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코드

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

https://github.com/salehiac/openballbot-rl

공식 코드

Reinforcement Learning for Ballbot Navigation in Uneven Terrain

https://github.com/salesforce/GAEA

공식 코드

GAEA: Graph Augmentation for Equitable Access via Reinforcement Learning

https://github.com/salesforce/MultiHopKG

공식 코드

Multi-Hop Knowledge Graph Reasoning with Reward Shaping

https://github.com/salesforce/WikiSQL

공식 코드

Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

https://github.com/salesforce/ai-economist

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The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning

https://github.com/salesforce/coderl

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CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning

https://github.com/salesforce/rirl

공식 코드

Solving Dynamic Principal-Agent Problems with a Rationally Inattentive Principal

https://github.com/salesforce/warp-drive

공식 코드

WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU

https://github.com/salwamostafa/intent-aware-drl-based-noma-uplink-dynamic-scheduler-for-iiot

공식 코드

Intent-Aware DRL-Based NOMA Uplink Dynamic Scheduler for IIoT

https://github.com/samindaa/RLLib

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Off-Policy General Value Functions to Represent Dynamic Role Assignments in RoboCup 3D Soccer Simulation

https://github.com/samlobel/RaCT_CF

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Towards Amortized Ranking-Critical Training for Collaborative Filtering

https://github.com/samlobel/cfn

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Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning

https://github.com/sampo-kuutti/training-adversarial-agents

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Training Adversarial Agents to Exploit Weaknesses in Deep Control Policies

https://github.com/sampo-kuutti/weakly-supervised-rl-highway-driving

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Weakly Supervised Reinforcement Learning for Autonomous Highway Driving via Virtual Safety Cages

https://github.com/samsungsailmontreal/stgg-al

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Generating $π$-Functional Molecules Using STGG+ with Active Learning

https://github.com/samuela/e-stops

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Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation

https://github.com/samuelmallick/mpcrl-greenhouse

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Reinforcement Learning-based Model Predictive Control for Greenhouse Climate Control

https://github.com/samuelschmidgall/surgicalgym

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Surgical Gym: A high-performance GPU-based platform for reinforcement learning with surgical robots

https://github.com/samuki/reinforce-joey

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Revisiting the Weaknesses of Reinforcement Learning for Neural Machine Translation

https://github.com/samysam0/babee

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Secure Control Systems for Autonomous Quadrotors against Cyber-Attacks

https://github.com/sangdon/PAC-confidence-set

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PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction

https://github.com/sangwkim/RL_manufacturing

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Dynamic Control of a Fiber Manufacturing Process using Deep Reinforcement Learning

https://github.com/sanketkshah/NeurADP-for-Ride-Pooling

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Neural Approximate Dynamic Programming for On-Demand Ride-Pooling

https://github.com/sarah-keren/rlpe

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Explainable Reinforcement Learning via Model Transforms

https://github.com/sarodyatawatta/hintrl

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Hint assisted reinforcement learning: an application in radio astronomy

https://github.com/sastpg/covo

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Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning

https://github.com/satchitchatterji/shieldedmarlthesis

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Think Smart, Act SMARL! Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learning

https://github.com/sbhakim/ansr-dt

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ANSR-DT: An Adaptive Neuro-Symbolic Learning and Reasoning Framework for Digital Twins

https://github.com/scale-lab/DRiLLS

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DRiLLS: Deep Reinforcement Learning for Logic Synthesis

https://github.com/schafert/inverse-irl-guppy

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Bayesian Inverse Reinforcement Learning for Collective Animal Movement

https://github.com/schatty/mocco

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Guided Exploration in Reinforcement Learning via Monte Carlo Critic Optimization

https://github.com/schroederdewitt/mackrl

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Multi-Agent Common Knowledge Reinforcement Learning

https://github.com/schroederdewitt/multiagent_mujoco

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FACMAC: Factored Multi-Agent Centralised Policy Gradients

https://github.com/schuderer/bprl

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Sim-Env: Decoupling OpenAI Gym Environments from Simulation Models

https://github.com/schwallergroup/saturn

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It Takes Two to Tango: Directly Optimizing for Constrained Synthesizability in Generative Molecular Design

https://github.com/scientific-computing-lab-nrcn/rlopenneomc

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Reactor Optimization Benchmark by Reinforcement Learning

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