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 Unity.MLAgents.Sensors;
namespace Unity.MLAgentsExamples
{
/// <summary>
/// A simple sensor that provides a number default implementations.
/// </summary>
public abstract class SensorBase : ISensor
{
/// <summary>
/// Write the observations to the output buffer. This size of the buffer will be product
/// of the sizes returned by <see cref="GetObservationShape"/>.
/// </summary>
/// <param name="output"></param>
public abstract void WriteObservation(float[] output);
/// <inheritdoc/>
public abstract int[] GetObservationShape();
/// <inheritdoc/>
public abstract string GetName();
/// <summary>
/// Default implementation of Write interface. This creates a temporary array,
/// calls WriteObservation, and then writes the results to the ObservationWriter.
/// </summary>
/// <param name="writer"></param>
/// <returns>The number of elements written.</returns>
public virtual int Write(ObservationWriter writer)
{
// TODO reuse buffer for similar agents, don't call GetObservationShape()
var numFloats = this.ObservationSize();
float[] buffer = new float[numFloats];
WriteObservation(buffer);
writer.AddRange(buffer);
return numFloats;
}
/// <inheritdoc/>
public void Update() { }
/// <inheritdoc/>
public void Reset() { }
/// <inheritdoc/>
public virtual byte[] GetCompressedObservation()
{
return null;
}
/// <inheritdoc/>
public virtual SensorCompressionType GetCompressionType()
{
return SensorCompressionType.None;
}
}
}