policy
GridDQN
Thiruvel-AP · PyTorch
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Overview
Name
GridDQN
Author
Thiruvel-AP
Framework
PyTorch
License
unknown
Skill type
navigation
Evidence level
untested
Task description
This project is to train an agent in a custom grid world with Deep Q-Network (DQN) from scratch. The agent learns optimal paths via reward-driven exploration and converges to a stable policy for shortest-path navigation.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
20clearpath-robotics-ladybug-5-ddmnot in seedclearpath-robotics-sick-lms111not in seedclearpath-robotics-husky-robotic-platformnot in seedclearpath-robotics-jackal-ugv-platformnot in seedclearpath-robotics-all-accessoriesnot in seedclearpath-robotics-industrialnot in seedclearpath-robotics-clearpath-careersnot in seedclearpath-robotics-husky-a300-amp-thumbnailnot in seedclearpath-robotics-observer-shadow-194not in seedclearpath-robotics-turtlebot-personal-robotnot in seedclearpath-robotics-autonomy-research-kit-imagenot in seedclearpath-robotics-new-corporate-our-storynot in seedclearpath-robotics-clearpath-roboticsnot in seedclearpath-robotics-otto-heavy-load-material-transporternot in seedclearpath-robotics-boxerugv-menunot in seedflybodynot in seedclearpath-robotics-warthog-menunot in seedclearpath-robotics-3d-lidar-dropdownnot in seedclearpath-robotics-ddm-imunot in seedclearpath-robotics-huskya300-menu-imagenot in seed
Compatible environments
0No environments list GridDQN yet.
Datasets that reference this policy
0No datasets reference GridDQN yet.