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OpenAI Gym
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An open-source toolkit from OpenAI that implements several Reinforcement Learning benchmarks including: classic control, Atari, Robotics and MuJoCo tasks.
(Description by Evolutionary learning of interpretable decision trees)
(Image Credit: OpenAI Gym)
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
HDDLGym: A Tool for Studying Multi-Agent Hierarchical Problems Defined in HDDL with OpenAI Gym
STITCH-OPE: Trajectory Stitching with Guided Diffusion for Off-Policy Evaluation
Bellman operator convergence enhancements in reinforcement learning algorithms
Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLM
ReaCritic: Large Reasoning Transformer-based DRL Critic-model Scaling For Heterogeneous Networks
IN-RIL: Interleaved Reinforcement and Imitation Learning for Policy Fine-Tuning
Learning global control of underactuated systems with Model-Based Reinforcement Learning
Real-Time Model Predictive Control for the Swing-Up Problem of an Underactuated Double Pendulum
Mining-Gym: A Configurable RL Benchmarking Environment for Truck Dispatch Scheduling
Optimizing 2D+1 Packing in Constrained Environments Using Deep Reinforcement Learning
Low-cost Real-world Implementation of the Swing-up Pendulum for Deep Reinforcement Learning Experiments
Value-Based Deep RL Scales Predictably
Illuminating Spaces: Deep Reinforcement Learning and Laser-Wall Partitioning for Architectural Layout Generation
Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning
RobotDiffuse: Motion Planning for Redundant Manipulator based on Diffusion Model
Robustness Evaluation of Offline Reinforcement Learning for Robot Control Against Action Perturbations
Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning
A quantum-classical reinforcement learning model to play Atari games
Optimizing Sensor Redundancy in Sequential Decision-Making Problems
Creating Hierarchical Dispositions of Needs in an Agent
A Multi-Agent Reinforcement Learning Testbed for Cognitive Radio Applications
Asymptotic Analysis of Sample-averaged Q-learning
The Smart Buildings Control Suite: A Diverse Open Source Benchmark to Evaluate and Scale HVAC Control Policies for Sustainability
MAGICS: Adversarial RL with Minimax Actors Guided by Implicit Critic Stackelberg for Convergent Neural Synthesis of Robot Safety
Average-Reward Maximum Entropy Reinforcement Learning for Underactuated Double Pendulum Tasks
Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement Learning
HistoGym: A Reinforcement Learning Environment for Histopathological Image Analysis
Adaptive Planning with Generative Models under Uncertainty
Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms
A Comprehensive Guide to Combining R and Python code for Data Science, Machine Learning and Reinforcement Learning
Mamba as Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning
OMPO: A Unified Framework for RL under Policy and Dynamics Shifts
Linear Function Approximation as a Computationally Efficient Method to Solve Classical Reinforcement Learning Challenges
Traffic control using intelligent timing of traffic lights with reinforcement learning technique and real-time processing of surveillance camera images
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