module documentation
This Python module defines the RandomActionMechanism abstract base class, which formalizes
the concept of a random action mechanism in the context of reinforcement learning agents for graph
theory applications. A random action mechanism governs how often an agent selects a random action
instead of following its learned policy. The module also serves as a foundation for concrete random
action mechanisms that differ in how the random action probability is initialized and how it
evolves over the course of the learning process.
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This class inherits from the RandomActionMechanism class and represents a random action mechanism in which the probability of executing a random action is constant and specified at construction time. |
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This class inherits from the RandomActionMechanism class and represents a random action mechanism with an exponential-style adaptation rule. An initial random action probability is specified at construction time... |
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This class inherits from the RandomActionMechanism class and represents a random action mechanism in which random actions are never executed. The random action probability is identically equal to 0 throughout the entire learning process. |
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This abstract class encapsulates the concept of a random action mechanism in the context of an RL agent for graph theory applications. A random action mechanism controls the probability with which the agent selects a random action instead of an action prescribed by its policy... |