algorithms.qsom¶
The Q-SOM learning algorithm, leveraging 2 SOMs and a Q-Table.
The Self-Organizing Maps (SOMs) are used to handle the continuous and multi-dimensional state and action spaces, whereas the Q-Table learns the interests of actions in states.
- members:
Modules
This module defines a Q-SOM helper that is used as an entrypoint to simplify the instantiation of Q-SOM Agents from a Gym Environment. |
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This module implements a Q-SOM Agent, with the decision and learning algorithms that make the agent act based on the received observations from the environment. |
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This module defines Self-Organizing Maps, also known as Kohonen Maps. |