Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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using System;
using System.Linq;
using UnityEngine;
namespace Unity.MLAgents.Actuators
{
/// <summary>
/// A structure that wraps the <see cref="ActionSegment{T}"/>s for a particular <see cref="IActionReceiver"/> and is
/// used when <see cref="IActionReceiver.OnActionReceived"/> is called.
/// </summary>
public readonly struct ActionBuffers
{
/// <summary>
/// An empty action buffer.
/// </summary>
public static ActionBuffers Empty = new ActionBuffers(ActionSegment<float>.Empty, ActionSegment<int>.Empty);
/// <summary>
/// Holds the Continuous <see cref="ActionSegment{T}"/> to be used by an <see cref="IActionReceiver"/>.
/// </summary>
public ActionSegment<float> ContinuousActions { get; }
/// <summary>
/// Holds the Discrete <see cref="ActionSegment{T}"/> to be used by an <see cref="IActionReceiver"/>.
/// </summary>
public ActionSegment<int> DiscreteActions { get; }
/// <summary>
/// Create an <see cref="ActionBuffers"/> instance with discrete actions stored as a float array. This exists
/// to achieve backward compatibility with the former Agent methods which used a float array for both continuous
/// and discrete actions.
/// </summary>
/// <param name="discreteActions">The float array of discrete actions.</param>
/// <returns>An <see cref="ActionBuffers"/> instance initialized with a <see cref="DiscreteActions"/>
/// <see cref="ActionSegment{T}"/> initialized from a float array.</returns>
public static ActionBuffers FromDiscreteActions(float[] discreteActions)
{
return new ActionBuffers(ActionSegment<float>.Empty, discreteActions == null ? ActionSegment<int>.Empty
: new ActionSegment<int>(Array.ConvertAll(discreteActions,
x => (int)x)));
}
/// <summary>
/// Construct an <see cref="ActionBuffers"/> instance with the continuous and discrete actions that will
/// be used.
/// /// </summary>
/// <param name="continuousActions">The continuous actions to send to an <see cref="IActionReceiver"/>.</param>
/// <param name="discreteActions">The discrete actions to send to an <see cref="IActionReceiver"/>.</param>
public ActionBuffers(float[] continuousActions, int[] discreteActions)
: this(new ActionSegment<float>(continuousActions), new ActionSegment<int>(discreteActions)) { }
/// <summary>
/// Construct an <see cref="ActionBuffers"/> instance with the continuous and discrete actions that will
/// be used.
/// </summary>
/// <param name="continuousActions">The continuous actions to send to an <see cref="IActionReceiver"/>.</param>
/// <param name="discreteActions">The discrete actions to send to an <see cref="IActionReceiver"/>.</param>
public ActionBuffers(ActionSegment<float> continuousActions, ActionSegment<int> discreteActions)
{
ContinuousActions = continuousActions;
DiscreteActions = discreteActions;
}
/// <summary>
/// Construct an <see cref="ActionBuffers"/> instance with <see cref="ActionSpec"/>. All values are initialized to zeros.
/// /// </summary>
/// <param name="actionSpec">The <see cref="ActionSpec"/> to send to an <see cref="IActionReceiver"/>.</param>
public ActionBuffers(ActionSpec actionSpec)
: this(new ActionSegment<float>(new float[actionSpec.NumContinuousActions]),
new ActionSegment<int>(new int[actionSpec.NumDiscreteActions]))
{ }
/// <summary>
/// Create an <see cref="ActionBuffers"/> instance with ActionSpec and all actions stored as a float array.
/// </summary>
/// <param name="actionSpec"><see cref="ActionSpec"/> of the <see cref="ActionBuffers"/></param>
/// <param name="actions">The float array of all actions, including discrete and continuous actions.</param>
/// <returns>An <see cref="ActionBuffers"/> instance initialized with a <see cref="ActionSpec"/> and a float array.</returns>
internal static ActionBuffers FromActionSpec(ActionSpec actionSpec, float[] actions)
{
if (actions == null)
{
return ActionBuffers.Empty;
}
Debug.Assert(actions.Length == actionSpec.NumContinuousActions + actionSpec.NumDiscreteActions,
$"The length of '{nameof(actions)}' does not match the total size of ActionSpec.\n" +
$"{nameof(actions)}.Length: {actions.Length}\n" +
$"{nameof(actionSpec)}: {actionSpec.NumContinuousActions + actionSpec.NumDiscreteActions}");
ActionSegment<float> continuousActionSegment = ActionSegment<float>.Empty;
ActionSegment<int> discreteActionSegment = ActionSegment<int>.Empty;
int offset = 0;
if (actionSpec.NumContinuousActions > 0)
{
continuousActionSegment = new ActionSegment<float>(actions, 0, actionSpec.NumContinuousActions);
offset += actionSpec.NumContinuousActions;
}
if (actionSpec.NumDiscreteActions > 0)
{
int[] discreteActions = new int[actionSpec.NumDiscreteActions];
for (var i = 0; i < actionSpec.NumDiscreteActions; i++)
{
discreteActions[i] = (int)actions[i + offset];
}
discreteActionSegment = new ActionSegment<int>(discreteActions);
}
return new ActionBuffers(continuousActionSegment, discreteActionSegment);
}
/// <summary>
/// Clear the <see cref="ContinuousActions"/> and <see cref="DiscreteActions"/> segments to be all zeros.
/// </summary>
public void Clear()
{
ContinuousActions.Clear();
DiscreteActions.Clear();
}
/// <summary>
/// Check if the <see cref="ActionBuffers"/> is empty.
/// </summary>
/// <returns>Whether the buffers are empty.</returns>
public bool IsEmpty()
{
return ContinuousActions.IsEmpty() && DiscreteActions.IsEmpty();
}
/// <inheritdoc/>
public override bool Equals(object obj)
{
if (!(obj is ActionBuffers))
{
return false;
}
var ab = (ActionBuffers)obj;
return ab.ContinuousActions.SequenceEqual(ContinuousActions) &&
ab.DiscreteActions.SequenceEqual(DiscreteActions);
}
/// <inheritdoc/>
public override int GetHashCode()
{
unchecked
{
return (ContinuousActions.GetHashCode() * 397) ^ DiscreteActions.GetHashCode();
}
}
}
/// <summary>
/// An interface that describes an object that can receive actions from a Reinforcement Learning network.
/// </summary>
public interface IActionReceiver
{
/// <summary>
/// Method called in order too allow object to execute actions based on the
/// <see cref="ActionBuffers"/> contents. The structure of the contents in the <see cref="ActionBuffers"/>
/// are defined by the <see cref="ActionSpec"/>.
/// </summary>
/// <param name="actionBuffers">The data structure containing the action buffers for this object.</param>
void OnActionReceived(ActionBuffers actionBuffers);
/// <summary>
/// Implement `WriteDiscreteActionMask()` to modify the masks for discrete
/// actions. When using discrete actions, the agent will not perform the masked
/// action.
/// </summary>
/// <param name="actionMask">
/// The action mask for the agent.
/// </param>
/// <remarks>
/// When using Discrete Control, you can prevent the Agent from using a certain
/// action by masking it with <see cref="IDiscreteActionMask.SetActionEnabled"/>.
///
/// See [Agents - Actions] for more information on masking actions.
///
/// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_14_docs/docs/Learning-Environment-Design-Agents.md#actions
/// </remarks>
/// <seealso cref="IActionReceiver.OnActionReceived"/>
void WriteDiscreteActionMask(IDiscreteActionMask actionMask);
}
}