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quick:agents [2020/02/18 15:05] – [Setting-Up the execution with Behavior Bricks] jesusmayoral | quick:agents [2020/02/20 10:26] – [Setting-Up the execution with Behavior Bricks] jesusmayoral | ||
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- The second branch will be `MoveToGameObject` node with a `IsTargetClose` decorator. | - The second branch will be `MoveToGameObject` node with a `IsTargetClose` decorator. | ||
- | - In `IsTargetClose` set 17 as the close distance. For the `target` we will create a blackboard input parameter called `target`. | + | - In `IsTargetClose` set 15 as the close distance. For the `target` we will create a blackboard input parameter called `target`. |
- In `MoveToGameObject ` set `target` as the `target`. | - In `MoveToGameObject ` set `target` as the `target`. | ||
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- We have 2 continuous actions, one to rotate and one to shoot, that is the space size. | - We have 2 continuous actions, one to rotate and one to shoot, that is the space size. | ||
- | You need to train our Enemy for having a proper behavior, but, for now, we give you a trained model that you can set in the `Behavior parameters` | + | You need to train our Enemy for having a proper behavior, but, for now, we give you a trained model that you can set in the `Behavior parameters` |
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## Training | ## Training | ||
- | The node used to execute `ML-Agents` in `Behavior Bricks` lets also to train a behavior inside a behavior tree. To do so, the only thing that has to be done is to check the control checkbox in the academy in the brain that we want to train. | + | The node used to execute `ML-Agents` in `Behavior Bricks` lets also to train a behavior inside a behavior tree. To do so, We have to follow the same procedure as indicated in [ML-Agents guides.](https:// |
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- | Then we have to follow the same procedure as indicated in [ML-Agents guides.](https:// | + |