Method OnActionReceived
OnActionReceived(ActionBuffers)
Implement OnActionReceived() to specify agent behavior at every step, based
on the provided action.
Declaration
public virtual void OnActionReceived(ActionBuffers actions)Parameters
| Type | Name | Description |
|---|---|---|
| ActionBuffers | actions | Struct containing the buffers of actions to be executed at this step. |
Implements
Remarks
An action is passed to this function in the form of an ActionBuffers. Your implementation must use the array to direct the agent's behavior for the current step.
You decide how many elements you need in the ActionBuffers to control your agent and what each element means. For example, if you want to apply a force to move an agent around the environment, you can arbitrarily pick three values in ActionBuffers.ContinuousActions array to use as the force components. During training, the agent's policy learns to set those particular elements of the array to maximize the training rewards the agent receives. (Of course, if you implement a Heuristic(in ActionBuffers) function, it must use the same elements of the action array for the same purpose since there is no learning involved.)
An Agent can use continuous and/or discrete actions. Configure this along with the size of the action array, in the BrainParameters of the agent's associated BehaviorParameters component.
When an agent uses continuous actions, the values in the ActionBuffers.ContinuousActions array are floating point numbers. You should clamp the values to the range, -1..1, to increase numerical stability during training.
When an agent uses discrete actions, the values in the ActionBuffers.DiscreteActions array are integers that each represent a specific, discrete action. For example, you could define a set of discrete actions such as:
0 = Do nothing
1 = Move one space left
2 = Move one space right
3 = Move one space up
4 = Move one space downWhen making a decision, the agent picks one of the five actions and puts the corresponding integer value in the ActionBuffers.DiscreteActions array. For example, if the agent decided to move left, the ActionBuffers.DiscreteActions parameter would be an array with a single element with the value 1.
You can define multiple sets, or branches, of discrete actions to allow an agent to perform simultaneous, independent actions. For example, you could use one branch for movement and another branch for throwing a ball left, right, up, or down, to allow the agent to do both in the same step.
The ActionBuffers.DiscreteActions array of an agent with discrete actions contains one element for each branch. The value of each element is the integer representing the chosen action for that branch. The agent always chooses one action for each branch.
When you use the discrete actions, you can prevent the training process or the neural network model from choosing specific actions in a step by implementing the WriteDiscreteActionMask(IDiscreteActionMask) method. For example, if your agent is next to a wall, you could mask out any actions that would result in the agent trying to move into the wall.
For more information about implementing agent actions see Agents - Actions.