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└── rrt_3D
├── rrt3D.py # rrt3D : goal-biased rrt3D
└── rrtstar3D.py
- └── Stochastic Shortest Path
- ├── value_iteration.py # value iteration
- ├── policy_iteration.py # policy iteration
- ├── Q-value_iteration.py # Q-value iteration
- └── Q-policy_iteration.py # Q-policy iteration
- └── Model-free Control
- ├── Sarsa.py # SARSA : on-policy TD control
- └── Q-learning.py # Q-learning : off-policy TD control
## Animations - Search-Based
### Best-First & Dijkstra
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-### Value/Policy/Q-value/Q-policy Iteration
-* Brown: losing states
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-### SARSA(on-policy) & Q-learning(off-policy)
-* Brown: losing states
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## Papers
### Search-base Planning
* [A*: ](https://ieeexplore.ieee.org/document/4082128) A Formal Basis for the Heuristic Determination of Minimum Cost Paths