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