policy
Self-driving-cars-with-Deep-Reinforcement-Learning-
VarshiniAG · PyTorch
or hover any field below to flag it
Overview
Name
Self-driving-cars-with-Deep-Reinforcement-Learning-
Author
VarshiniAG
Framework
PyTorch
License
unknown
Skill type
navigation
Evidence level
untested
Task description
Reinforcement Learning for Taxi-v2 (self-driving cab simulation). Implemented Q-learning using OpenAI Gym to train a smart cab to safely navigate, pick up, and drop off passengers efficiently. Demonstrates RL concepts like exploration, policy learning, and optimal action selection.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
20anybotics-anymal-cnot in seedalohanot in seedgoogle-barkour-vbnot in seedboston-dynamics-spotnot in seedfranka-fr3not in seedgoogle-barkour-v0not in seedagilex-pipernot in seedberkeley-humanoidnot in seedbitcraze-crazyflie-2not in seedanybotics-anymal-bnot in seedagility-cassienot in seedarx-l5not in seedbooster-t1not in seedfranka-emika-pandanot in seedfranka-fr3-v2not in seeddynamixel-2rnot in seedflexiv-rizon4not in seedassetsnot in seedapptronik-apollonot in seedfourier-n1not in seed
Compatible environments
0No environments list Self-driving-cars-with-Deep-Reinforcement-Learning- yet.
Datasets that reference this policy
0No datasets reference Self-driving-cars-with-Deep-Reinforcement-Learning- yet.