API Reference - Models - DeepQLearning (DQN)

DeepQLearning is a neural network with reinforcement learning capabilities. It can predict any positive numbers of discrete values.

Constructors

new()

Create new model object. If any of the arguments are nil, default argument values for that argument will be used.

DeepQLearning.new(discountFactor: number): ModelObject

Parameters:

• lambda: At 0, the model acts like the Temporal Difference algorithm. At 1, the model acts as Monte Carlo algorithm. Between 0 and 1, the model acts as both. [Default: 0]

• discountFactor: The higher the value, the more likely it focuses on long-term outcomes. The value must be set between 0 and 1. [Default: 0.95]

Returns:

• ModelObject: The generated model object.

Inherited From

• ReinforcementLearningBaseModel

References

• Reinforcement Learning with Neural Network

• Reinforcement Q-Learning from Scratch in Python with OpenAI Gym