https://github.com/umd-huang-lab/wocar-rl
공식 코드Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning
Papers with Code 아카이브
Reinforcement Learning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/umenberger/robust-exploration
공식 코드Robust exploration in linear quadratic reinforcement learning
https://github.com/umrobotslang/does-drl-learn-to-navigate
공식 코드A Critical Investigation of Deep Reinforcement Learning for Navigation
https://github.com/unc-optimization/ProxHSPGA
공식 코드A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning
https://github.com/uncharted-technologies/robust-domain-randomization
공식 코드Robust Visual Domain Randomization for Reinforcement Learning
https://github.com/unstable-zeros/learning-cbfs
공식 코드Learning Control Barrier Functions from Expert Demonstrations
https://github.com/uoe-agents/LIAM
공식 코드Agent Modelling under Partial Observability for Deep Reinforcement Learning
https://github.com/uoe-agents/cmid
공식 코드Conditional Mutual Information for Disentangled Representations in Reinforcement Learning
https://github.com/uoe-agents/derl
공식 코드Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration
https://github.com/uoe-agents/epymarl
공식 코드Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks
https://github.com/uoe-agents/lb-foraging
공식 코드Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning
https://github.com/uoe-agents/mvd
공식 코드Multi-view Disentanglement for Reinforcement Learning with Multiple Cameras
https://github.com/uoe-agents/pressureplate
공식 코드Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy Optimization
https://github.com/uoe-agents/robotic-warehouse
공식 코드Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks
https://github.com/uoe-agents/sami
공식 코드Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning
https://github.com/uoe-agents/seac
공식 코드Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning
https://github.com/uoe-agents/seps
공식 코드Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
https://github.com/uoe-agents/smaclite
공식 코드SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning
https://github.com/uoe-agents/ted
공식 코드Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning
https://github.com/upb-lea/gym-electric-motor
공식 코드Towards a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control
https://github.com/usc-psychsim/mirl-tom-aamas23
공식 코드Multiagent Inverse Reinforcement Learning via Theory of Mind Reasoning
https://github.com/ushaham/adaptiveFS
공식 코드Learning to Ask Medical Questions using Reinforcement Learning
https://github.com/ustchlsong/ma2cl
공식 코드MA2CL:Masked Attentive Contrastive Learning for Multi-Agent Reinforcement Learning
https://github.com/ut-austin-rpl/amago
공식 코드AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
https://github.com/utiasDSL/gym-pybullet-drones
공식 코드https://github.com/utiasDSL/safe-control-gym
공식 코드Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning
https://github.com/utiasSTARS/vpace
공식 코드Efficient Imitation Without Demonstrations via Value-Penalized Auxiliary Control from Examples
https://github.com/utsavz/piper
공식 코드https://github.com/uuujf/GapExploration
공식 코드Gap-Dependent Unsupervised Exploration for Reinforcement Learning
https://github.com/uzh-rpg/cl_initial_buffer
공식 코드https://github.com/uzh-rpg/flightmare
공식 코드https://github.com/uzh-rpg/rl_vo
공식 코드https://github.com/uzkent/EfficientObjectDetection
공식 코드Efficient Object Detection in Large Images using Deep Reinforcement Learning
https://github.com/vadim0x60/cibi-experiments
공식 코드Neurogenetic Programming Framework for Explainable Reinforcement Learning
https://github.com/valarzz/dlpa
공식 코드Model-based Reinforcement Learning for Parameterized Action Spaces
https://github.com/valarzz/model-based-reinforcement-learning-for-parameterized-action-spaces
공식 코드Model-based Reinforcement Learning for Parameterized Action Spaces
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.