/// [OnDisable()]: https://docs.unity3d.com/ScriptReference/MonoBehaviour.OnDisable.html]
/// [OnBeforeSerialize()]: https://docs.unity3d.com/ScriptReference/MonoBehaviour.OnBeforeSerialize.html
/// [OnAfterSerialize()]: https://docs.unity3d.com/ScriptReference/MonoBehaviour.OnAfterSerialize.html
/// [Agents]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design-Agents.md
/// [Reinforcement Learning in Unity]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design.md
/// [Agents]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design-Agents.md
/// [Reinforcement Learning in Unity]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design.md
/// [Unity ML-Agents Toolkit manual]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Readme.md
/// [Unity ML-Agents Toolkit manual]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Readme.md
[ HelpURL ( "https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/" +
[ HelpURL ( "https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/" +
"docs/Learning-Environment-Design-Agents.md" ) ]
[Serializable]
[RequireComponent(typeof(BehaviorParameters))]
/// for information about mixing reward signals from curiosity and Generative Adversarial
/// Imitation Learning (GAIL) with rewards supplied through this method.
///
/// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design-Agents.md#rewards
/// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
/// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design-Agents.md#rewards
/// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
/// </remarks>
/// <param name="reward">The new value of the reward.</param>
public void SetReward ( float reward )
/// for information about mixing reward signals from curiosity and Generative Adversarial
/// Imitation Learning (GAIL) with rewards supplied through this method.
///
/// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design-Agents.md#rewards
/// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
/// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design-Agents.md#rewards
/// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
///</remarks>
/// <param name="increment">Incremental reward value.</param>
public void AddReward ( float increment )
/// implementing a simple heuristic function can aid in debugging agent actions and interactions
/// with its environment.
///
/// [Demonstration Recorder]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design-Agents.md#recording-demonstrations
/// [Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design-Agents.md#actions
/// [Demonstration Recorder]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design-Agents.md#recording-demonstrations
/// [Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design-Agents.md#actions
/// [GameObject]: https://docs.unity3d.com/Manual/GameObjects.html
/// </remarks>
/// <example>
/// For more information about observations, see [Observations and Sensors].
///
/// [GameObject]: https://docs.unity3d.com/Manual/GameObjects.html
/// [Observations and Sensors]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design-Agents.md#observations-and-sensors
/// [Observations and Sensors]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design-Agents.md#observations-and-sensors
/// </remarks>
public virtual void CollectObservations ( VectorSensor sensor )
{
///
/// See [Agents - Actions] for more information on masking actions.
///
/// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design-Agents.md#actions
/// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design-Agents.md#actions
/// </remarks>
/// <seealso cref="OnActionReceived(float[])"/>
public virtual void CollectDiscreteActionMasks ( DiscreteActionMasker actionMasker )
///
/// For more information about implementing agent actions see [Agents - Actions].
///
/// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_5 _docs/docs/Learning-Environment-Design-Agents.md#actions
/// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_6 _docs/docs/Learning-Environment-Design-Agents.md#actions
/// </remarks>
/// <param name="vectorAction">
/// An array containing the action vector. The length of the array is specified
Christopher Goy
4 年前