Papers with Code 아카이브

Deep Reinforcement Learning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 0
보존된 평가 기록: 0

코드

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

https://github.com/lmb-freiburg/td-or-not-td

공식 코드

TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning

https://github.com/lns/dapo

공식 코드

Divergence-Augmented Policy Optimization

https://github.com/lobiaminor/bpo_challenge_gdrl

공식 코드

Automated decision-making for dynamic task assignment at scale

https://github.com/lockwo/rl_qvc_opt

공식 코드

Optimizing Quantum Variational Circuits with Deep Reinforcement Learning

https://github.com/lollcat/DistillationTrain-Gym

공식 코드

Deep Reinforcement Learning for Process Synthesis

https://github.com/lqm00/a2p-sac

공식 코드

Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space

https://github.com/lucadellalib/sac-beta

공식 코드

Soft Actor-Critic with Beta Policy via Implicit Reparameterization Gradients

https://github.com/lucascjysdl/deepfreight

공식 코드

DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight Delivery

https://github.com/lucasmagnana/a-drl-solution-to-help-reduce-the-cost-in-waiting-time-of-securing-a-traffic-light-for-cyclists

공식 코드

A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclists

https://github.com/luciferkonn/moc_corl22

공식 코드

Learning Multi-Objective Curricula for Robotic Policy Learning

https://github.com/luckeciano/humanoid-run-ppo

공식 코드

Learning Humanoid Robot Running Skills through Proximal Policy Optimization

https://github.com/luisfelipewb/RL4WasteCapture

공식 코드

Evaluating Robustness of Deep Reinforcement Learning for Autonomous Surface Vehicle Control in Field Tests

https://github.com/luksfarris/pydeeprecsys

공식 코드

Optimized Recommender Systems with Deep Reinforcement Learning

https://github.com/machado-research/AgarCL

공식 코드

The Cell Must Go On: Agar.io for Continual Reinforcement Learning

https://github.com/machine-teaching-group/ijcai2024-proximal-curriculum-target-rl

공식 코드

Proximal Curriculum with Task Correlations for Deep Reinforcement Learning

https://github.com/malteschilling/ddrl_hexapod

공식 코드

Decentralized Deep Reinforcement Learning for a Distributed and Adaptive Locomotion Controller of a Hexapod Robot

https://github.com/manluow/ev-simulator

공식 코드

Fleet Rebalancing for Expanding Shared e-Mobility Systems: A Multi-agent Deep Reinforcement Learning Approach

https://github.com/manueleberhardinger/ec-rl

공식 코드

Learning of Generalizable and Interpretable Knowledge in Grid-Based Reinforcement Learning Environments

https://github.com/manueleberhardinger/unveiling-rl-with-gp

공식 코드

Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming

https://github.com/maohangyu/TIT_open_source

공식 코드

Transformer in Transformer as Backbone for Deep Reinforcement Learning

https://github.com/maohangyu/pdit

공식 코드

PDiT: Interleaving Perception and Decision-making Transformers for Deep Reinforcement Learning

https://github.com/maoubo/unidoor

공식 코드

UNIDOOR: A Universal Framework for Action-Level Backdoor Attacks in Deep Reinforcement Learning

https://github.com/maoxiaowei97/drl4route

공식 코드

DRL4Route: A Deep Reinforcement Learning Framework for Pick-up and Delivery Route Prediction

https://github.com/maoxiaowei97/dutytte

공식 코드

DutyTTE: Deciphering Uncertainty in Origin-Destination Travel Time Estimation

https://github.com/marcometer/endless-memory-gym

공식 코드

Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents

https://github.com/marikoisogawa/OpticalNLOSPose

공식 코드

Optical Non-Line-of-Sight Physics-based 3D Human Pose Estimation

https://github.com/mariuslindegaard/curiosity_baselines

공식 코드

Intrinsic Rewards from Self-Organizing Feature Maps for Exploration in Reinforcement Learning

https://github.com/marko-ruman/RL-Correspondence-Learner

공식 코드

Knowledge Transfer in Deep Reinforcement Learning via an RL-Specific GAN-Based Correspondence Function

https://github.com/marmotatzju/drl-based-trajectory-tracking

공식 코드

DRL-Based Trajectory Tracking for Motion-Related Modules in Autonomous Driving

https://github.com/marmotlab/SIGMA

공식 코드

SIGMA: Sheaf-Informed Geometric Multi-Agent Pathfinding

https://github.com/martinballa/sf-tr

공식 코드

Task Relabelling for Multi-task Transfer using Successor Features

https://github.com/marwaltz/tud_rl

공식 코드

Spatial-temporal recurrent reinforcement learning for autonomous ships

https://github.com/maryam-abdool/swim-control

공식 코드

Swim: A General-Purpose, High-Performing, and Efficient Activation Function for Locomotion Control Tasks

https://github.com/masa2203/battery_arbitrage_with_drl

공식 코드

Enhancing Battery Storage Energy Arbitrage with Deep Reinforcement Learning and Time-Series Forecasting

https://github.com/masud99r/thinker

공식 코드

Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning

https://github.com/matt00n/policygradientsjax

공식 코드

The Definitive Guide to Policy Gradients in Deep Reinforcement Learning: Theory, Algorithms and Implementations

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.