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+# [API Reference](../../API.md) - [Models](../Models.md) - REINFORCE
+
+MonteCarloControl 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.
+
+```
+MonteCarloControl.new({discountFactor: number}): ModelObject
+```
+
+#### Parameters:
+
+* discountFactor: The higher the value, the more likely it focuses on long-term outcomes. The value must be set between 0 and 1.
+
+#### Returns:
+
+* ModelObject: The generated model object.
+
+## Functions
+
+### setParameters()
+
+Set model's parameters. When any of the arguments are nil, previous argument values for that argument will be used.
+
+```
+MonteCarloControl:setParameters({discountFactor: number})
+```
+
+#### Parameters:
+
+* discountFactor: The higher the value, the more likely it focuses on long-term outcomes. The value must be set between 0 and 1.
+
+## Inherited From
+
+* [ReinforcementLearningBaseModel](ReinforcementLearningBaseModel.md)
+
+## References
+
+* [Forgetting Early Estimates in Monte Carlo Control Methods](https://ev.fe.uni-lj.si/3-2015/Vodopivec.pdf)
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