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83 行
2.7 KiB
83 行
2.7 KiB
using UnityEngine;
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using UnityEngine.Serialization;
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#if UNITY_EDITOR
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using UnityEditor;
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#endif
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namespace MLAgents
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{
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/// <summary>
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/// The Heuristic Brain type allows you to hand code an Agent's decision making process.
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/// A Heuristic Brain requires an implementation of the Decision interface to which it
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/// delegates the decision making process.
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/// When yusing a Heuristic Brain, you must give it a Monoscript of a Decision implementation.
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/// </summary>
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[CreateAssetMenu(fileName = "NewHeuristicBrain", menuName = "ML-Agents/Heuristic Brain")]
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public class HeuristicBrain : Brain
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{
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[SerializeField]
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[HideInInspector]
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public Decision decision;
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#if UNITY_EDITOR
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[HideInInspector]
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public MonoScript decisionScript;
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#endif
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[FormerlySerializedAs("c_decision")]
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[SerializeField]
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[HideInInspector]
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public string cDecision;
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public void OnValidate()
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{
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#if UNITY_EDITOR
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if (decisionScript != null)
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{
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cDecision = decisionScript.GetClass().Name;
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}
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else
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{
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cDecision = "";
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}
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#endif
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}
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/// <inheritdoc/>
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protected override void Initialize()
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{
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if ((cDecision != null) && decision == null)
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{
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decision = CreateInstance(cDecision) as Decision;
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decision.brainParameters = brainParameters;
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}
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}
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///Uses the Decision Component to decide that action to take
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protected override void DecideAction()
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{
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if (decision == null)
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{
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throw new UnityAgentsException(
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"The Brain is set to Heuristic, but no decision script attached to it");
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}
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foreach (var agent in m_AgentInfos.Keys)
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{
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agent.UpdateVectorAction(decision.Decide(
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m_AgentInfos[agent].stackedVectorObservation,
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m_AgentInfos[agent].visualObservations,
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m_AgentInfos[agent].reward,
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m_AgentInfos[agent].done,
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m_AgentInfos[agent].memories));
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}
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foreach (var agent in m_AgentInfos.Keys)
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{
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agent.UpdateMemoriesAction(decision.MakeMemory(
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m_AgentInfos[agent].stackedVectorObservation,
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m_AgentInfos[agent].visualObservations,
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m_AgentInfos[agent].reward,
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m_AgentInfos[agent].done,
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m_AgentInfos[agent].memories));
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}
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m_AgentInfos.Clear();
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}
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}
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}
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