AABB
AlignmentBehavior
ArriveBehavior
AStar
BFS
BoundingSphere
BVH
BVHNode
Cell
CellSpacePartitioning
CohesionBehavior
CompositeGoal
ConvexHull
Corridor
CostTable
DFS
Dijkstra
Edge
EntityManager
EvadeBehavior
EventDispatcher
Behavior
FollowPathBehavior
FuzzyAND
FuzzyCompositeTerm
FuzzyFAIRLY
FuzzyModule
FuzzyOR
FuzzyRule
FuzzySet
FuzzyTerm
FuzzyVariable
FuzzyVERY
GameEntity
Goal
GoalEvaluator
Graph
GraphUtils
HalfEdge
HeuristicPolicyDijkstra
HeuristicPolicyEuclid
HeuristicPolicyEuclidSquared
HeuristicPolicyManhattan
InterposeBehavior
LeftSCurveFuzzySet
LeftShoulderFuzzySet
LineSegment
Logger
MathUtils
Matrix3
Matrix4
MemoryRecord
MemorySystem
MeshGeometry
MessageDispatcher
MovingEntity
NavEdge
NavMesh
NavMeshLoader
NavNode
Node
NormalDistFuzzySet
OBB
ObstacleAvoidanceBehavior
OffsetPursuitBehavior
OnPathBehavior
Path
Plane
Polygon
Polyhedron
PriorityQueue
PursuitBehavior
Quaternion
Ray
RectangleTriggerRegion
Regular
RightSCurveFuzzySet
RightShoulderFuzzySet
SAT
SeekBehavior
SeparationBehavior
SingletonFuzzySet
Smoother
SphericalTriggerRegion
State
StateMachine
SteeringBehavior
SteeringManager
Task
TaskQueue
Telegram
Think
Time
TriangularFuzzySet
Trigger
TriggerRegion
Vector3
Vehicle
Version
WanderBehavior

toJSON

toJSON是Yuka js库中FuzzyAND模块的一个方法。该方法返回一个含有模糊量化和模糊控制规则的JSON对象,以便日后保存或导出。

语法

FuzzyAND.toJSON()

返回值

该方法返回一个JSON对象,包含以下属性:

  • variables: 包含每个变量的名称、偏移量和范围。
  • rules: 包含模糊控制规则的数组。每个规则都包含一个输入项、输出项和一个权重值。
  • andMethod: FuzzyAND使用的模糊AND方法的名称。
  • orMethod: FuzzyAND使用的模糊OR方法的名称。

例子

以下是FuzzyAND的toJSON方法的使用方法;

const myFuzzyAND = new YUKA.FuzzyAND();
//添加变量
const distance = myFuzzyAND.createVariable('distance', 0, 10);
const speed = myFuzzyAND.createVariable('speed', 0, 10);
const steering = myFuzzyAND.createVariable('steering', -Math.PI, Math.PI);

//添加隶属函数
distance.addMembership('near', new YUKA.Triangle(0, 2.5, 5));
distance.addMembership('medium', new YUKA.Triangle(2.5, 5, 7.5));
distance.addMembership('far', new YUKA.Triangle(5, 7.5, 10));

speed.addMembership('slow', new YUKA.Triangle(0, 2.5, 5));
speed.addMembership('medium', new YUKA.Triangle(2.5, 5, 7.5));
speed.addMembership('fast', new YUKA.Triangle(5, 7.5, 10));

steering.addMembership('sharpLeft', new YUKA.Trapezoid(-Math.PI, -Math.PI, -Math.PI / 2, -Math.PI / 4));
steering.addMembership('left', new YUKA.Triangle(-Math.PI / 2, -Math.PI / 4, 0));
steering.addMembership('straightAhead', new YUKA.Triangle(-Math.PI / 4, 0, Math.PI / 4));
steering.addMembership('right', new YUKA.Triangle(0, Math.PI / 4, Math.PI / 2));
steering.addMembership('sharpRight', new YUKA.Trapezoid(Math.PI / 2, Math.PI / 4, Math.PI, Math.PI));

//添加规则
myFuzzyAND.addRule(
  new YUKA.FuzzyRule(
    new YUKA.FuzzyAND(
      new YUKA.FuzzyTerm(distance.terms['near']),
      new YUKA.FuzzyTerm(speed.terms['fast'])
    ),
    steering.terms['sharpLeft'],
    1
  )
);

myFuzzyAND.addRule(
  new YUKA.FuzzyRule(
    new YUKA.FuzzyAND(
      new YUKA.FuzzyTerm(distance.terms['medium']),
      new YUKA.FuzzyTerm(speed.terms['medium'])
    ),
    steering.terms['straightAhead'],
    1
  )
);

myFuzzyAND.addRule(
  new YUKA.FuzzyRule(
    new YUKA.FuzzyAND(
      new YUKA.FuzzyTerm(distance.terms['far']),
      new YUKA.FuzzyTerm(speed.terms['slow'])
    ),
    steering.terms['sharpRight'],
    1
  )
);

//导出为JSON
const json = myFuzzyAND.toJSON();

导出的JSON对象如下:

{
  "variables": {
    "distance": {
      "min": 0,
      "max": 10,
      "offset": 0,
      "terms": [
        {
          "name": "near",
          "func": {
            "type": "Triangle",
            "points": [
              0,
              0,
              2.5
            ]
          }
        },
        {
          "name": "medium",
          "func": {
            "type": "Triangle",
            "points": [
              2.5,
              5,
              7.5
            ]
          }
        },
        {
          "name": "far",
          "func": {
            "type": "Triangle",
            "points": [
              5,
              7.5,
              10
            ]
          }
        }
      ]
    },
    "speed": {
      "min": 0,
      "max": 10,
      "offset": 0,
      "terms": [
        {
          "name": "slow",
          "func": {
            "type": "Triangle",
            "points": [
              0,
              0,
              2.5
            ]
          }
        },
        {
          "name": "medium",
          "func": {
            "type": "Triangle",
            "points": [
              2.5,
              5,
              7.5
            ]
          }
        },
        {
          "name": "fast",
          "func": {
            "type": "Triangle",
            "points": [
              5,
              7.5,
              10
            ]
          }
        }
      ]
    },
    "steering": {
      "min": -3.141592653589793,
      "max": 3.141592653589793,
      "offset": 0,
      "terms": [
        {
          "name": "sharpLeft",
          "func": {
            "type": "Trapezoid",
            "points": [
              -3.141592653589793,
              -3.141592653589793,
              -1.5707963267948966,
              -0.7853981633974483
            ]
          }
        },
        {
          "name": "left",
          "func": {
            "type": "Triangle",
            "points": [
              -1.5707963267948966,
              -0.7853981633974483,
              0
            ]
          }
        },
        {
          "name": "straightAhead",
          "func": {
            "type": "Triangle",
            "points": [
              -0.7853981633974483,
              0,
              0.7853981633974483
            ]
          }
        },
        {
          "name": "right",
          "func": {
            "type": "Triangle",
            "points": [
              0,
              0.7853981633974483,
              1.5707963267948966
            ]
          }
        },
        {
          "name": "sharpRight",
          "func": {
            "type": "Trapezoid",
            "points": [
              1.5707963267948966,
              0.7853981633974483,
              3.141592653589793,
              3.141592653589793
            ]
          }
        }
      ]
    }
  },
  "rules": [
    {
      "input": {
        "type": "FuzzyAND",
        "terms": [
          {
            "type": "FuzzyTerm",
            "variable": "distance",
            "termName": "near"
          },
          {
            "type": "FuzzyTerm",
            "variable": "speed",
            "termName": "fast"
          }
        ]
      },
      "output": {
        "type": "FuzzyTerm",
        "variable": "steering",
        "termName": "sharpLeft"
      },
      "weight": 1
    },
    {
      "input": {
        "type": "FuzzyAND",
        "terms": [
          {
            "type": "FuzzyTerm",
            "variable": "distance",
            "termName": "medium"
          },
          {
            "type": "FuzzyTerm",
            "variable": "speed",
            "termName": "medium"
          }
        ]
      },
      "output": {
        "type": "FuzzyTerm",
        "variable": "steering",
        "termName": "straightAhead"
      },
      "weight": 1
    },
    {
      "input": {
        "type": "FuzzyAND",
        "terms": [
          {
            "type": "FuzzyTerm",
            "variable": "distance",
            "termName": "far"
          },
          {
            "type": "FuzzyTerm",
            "variable": "speed",
            "termName": "slow"
          }
        ]
      },
      "output": {
        "type": "FuzzyTerm",
        "variable": "steering",
        "termName": "sharpRight"
      },
      "weight": 1
    }
  ],
  "andMethod": "min",
  "orMethod": "max"
}

参考