环境仿真软件：AnyLogic_（4）.Agent建模方法
Agent是AnyLogic中用于表示系统中具有自主行为的个体的基本单元。每个Agent可以拥有自己的状态、属性、方法和事件。Agent可以与其他Agent或环境进行交互，从而形成复杂的系统行为。Agent的典型应用包括模拟人群、车辆、动物、企业等。Agent建模方法在AnyLogic中提供了强大的工具，用于模拟复杂系统中的个体行为及其相互作用。通过定义Agent的属性、方法和事件，可以构建出高度
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Agent建模方法
在AnyLogic中，Agent建模方法是一种强大的技术，用于模拟复杂系统中的个体行为及其相互作用。Agent建模方法的核心思想是将系统中的每个个体视为一个独立的代理（Agent），每个代理都有自己的状态、行为和决策规则。通过定义这些代理及其交互规则，可以构建出高度复杂的仿真模型，从而更好地理解和预测系统的动态行为。
1. Agent的基本概念
1.1 什么是Agent
Agent是AnyLogic中用于表示系统中具有自主行为的个体的基本单元。每个Agent可以拥有自己的状态、属性、方法和事件。Agent可以与其他Agent或环境进行交互，从而形成复杂的系统行为。Agent的典型应用包括模拟人群、车辆、动物、企业等。
1.2 Agent的属性和方法
1.2.1 属性
Agent的属性是用于描述Agent状态的变量。这些属性可以是数值型、布尔型、字符串型或自定义类型。例如，一个模拟人群的Agent可能包含以下属性：
-
age：年龄 -
gender：性别 -
position：当前位置 -
velocity：速度 -
destination：目标位置
1.2.2 方法
Agent的方法是用于定义其行为的函数。这些方法可以包括初始化、移动、决策等。例如，一个模拟人群的Agent可能包含以下方法：
-
initialize()：初始化Agent的状态 -
move()：移动到目标位置 -
decideNextDestination()：决定下一个目标位置
1.3 Agent的事件
Agent的事件是用于触发特定行为的机制。事件可以是定时事件、条件事件或外部事件。例如，一个模拟人群的Agent可能包含以下事件：
-
onEnterRoom()：进入房间时触发的事件 -
onLeaveRoom()：离开房间时触发的事件 -
onTimer()：定时触发的事件，用于定期更新Agent的状态
2. 创建和管理Agent
2.1 创建Agent类
在AnyLogic中，创建Agent类通常涉及以下步骤：
-
打开AnyLogic并创建一个新的模型。
-
在模型中添加一个新的Agent类。
-
定义Agent类的属性、方法和事件。
2.1.1 示例：创建一个模拟人群的Agent类
假设我们正在创建一个模拟人群的Agent类，名为Person。以下是创建Person类的步骤：
// 定义Person类
public class Person extends Agent {
// 定义属性
private double age;
private String gender;
private Point position;
private double velocity;
private Point destination;
// 定义方法
public void initialize(double age, String gender, Point position, double velocity, Point destination) {
this.age = age;
this.gender = gender;
this.position = position;
this.velocity = velocity;
this.destination = destination;
}
public void move() {
// 计算新的位置
position = new Point(position.getX() + velocity * (destination.getX() - position.getX()),
position.getY() + velocity * (destination.getY() - position.getY()));
}
public void decideNextDestination(List<Point> possibleDestinations) {
// 随机选择下一个目标位置
destination = possibleDestinations.get(uniform(0, possibleDestinations.size() - 1));
}
// 定义事件
public void onEnterRoom(Room room) {
// 进入房间时的行为
System.out.println("Person " + this.getId() + " entered " + room.getName());
}
public void onLeaveRoom(Room room) {
// 离开房间时的行为
System.out.println("Person " + this.getId() + " left " + room.getName());
}
public void onTimer() {
// 定时更新Agent的状态
this.move();
}
}
2.2 管理Agent实例
在AnyLogic中，可以通过创建Agent集合来管理多个Agent实例。Agent集合可以是静态的或动态的，具体取决于模型的需求。
2.2.1 创建Agent集合
// 定义Agent集合
public class Main extends Agent {
private List<Person> people;
public void createPeople(int count, List<Point> possibleDestinations) {
people = new ArrayList<>();
for (int i = 0; i < count; i++) {
double age = uniform(18, 60);
String gender = uniform(0, 1) < 0.5 ? "Male" : "Female";
Point position = new Point(uniform(0, 100), uniform(0, 100));
double velocity = uniform(1, 5);
Point destination = possibleDestinations.get(uniform(0, possibleDestinations.size() - 1));
Person person = new Person();
person.initialize(age, gender, position, velocity, destination);
people.add(person);
}
}
public void startSimulation() {
// 启动定时器，每秒更新一次所有Agent的状态
addEvent(new Event() {
@Override
public void action() {
for (Person person : people) {
person.onTimer();
}
}
});
}
}
2.3 Agent的初始化
Agent的初始化通常在模型的主类中进行。通过初始化，可以设置Agent的初始状态，包括属性和位置。
2.3.1 示例：初始化Agent集合
public class Main extends Agent {
private List<Person> people;
private List<Point> possibleDestinations;
public void initialize() {
// 定义可能的目标位置
possibleDestinations = Arrays.asList(
new Point(50, 50),
new Point(70, 70),
new Point(30, 30)
);
// 创建100个Person实例
createPeople(100, possibleDestinations);
// 启动仿真
startSimulation();
}
}
3. Agent之间的交互
3.1 交互机制
Agent之间的交互可以通过消息传递、共享资源或直接方法调用等方式实现。在AnyLogic中，常用的消息传递机制包括事件触发和消息队列。
3.1.1 消息传递
消息传递是一种常见的Agent交互方式。通过发送和接收消息，Agent可以与其他Agent进行通信。
3.2 示例：Agent之间的消息传递
假设我们有一个模拟交通的模型，其中包含两个Agent类：Car和TrafficLight。Car需要根据TrafficLight的信号决定是否停止或继续行驶。
// 定义Car类
public class Car extends Agent {
private Point position;
private double velocity;
private TrafficLight currentTrafficLight;
public void initialize(Point position, double velocity, TrafficLight currentTrafficLight) {
this.position = position;
this.velocity = velocity;
this.currentTrafficLight = currentTrafficLight;
}
public void move() {
if (currentTrafficLight != null && currentTrafficLight.isRed()) {
// 如果当前交通灯是红灯，停止
velocity = 0;
} else {
// 否则，继续行驶
position = new Point(position.getX() + velocity, position.getY());
}
}
public void onTimer() {
this.move();
}
}
// 定义TrafficLight类
public class TrafficLight extends Agent {
private boolean isRed;
public void initialize(boolean isRed) {
this.isRed = isRed;
}
public boolean isRed() {
return isRed;
}
public void toggleLight() {
isRed = !isRed;
}
public void onTimer() {
// 每10秒切换一次交通灯
if (getEngine().getElapsedTime() % 10 == 0) {
toggleLight();
}
}
}
// 定义主类
public class Main extends Agent {
private List<Car> cars;
private TrafficLight trafficLight;
public void initialize() {
// 初始化交通灯
trafficLight = new TrafficLight();
trafficLight.initialize(true);
// 创建10个Car实例
cars = new ArrayList<>();
for (int i = 0; i < 10; i++) {
Point position = new Point(uniform(0, 100), 0);
double velocity = uniform(1, 5);
Car car = new Car();
car.initialize(position, velocity, trafficLight);
cars.add(car);
}
// 启动仿真
startSimulation();
}
public void startSimulation() {
// 启动交通灯的定时器
trafficLight.addEvent(new Event() {
@Override
public void action() {
trafficLight.onTimer();
}
});
// 启动所有Car的定时器
for (Car car : cars) {
car.addEvent(new Event() {
@Override
public void action() {
car.onTimer();
}
});
}
}
}
4. Agent与环境的交互
4.1 环境的概念
环境是指Agent所处的外部条件和资源。在AnyLogic中，环境可以通过地理空间、网络、数据库等方式表示。Agent可以与环境进行交互，从而影响其行为。
4.2 示例：Agent与地理空间的交互
假设我们有一个模拟森林火灾的模型，其中包含两个Agent类：Fire和Tree。Fire可以传播到周围的Tree，而Tree可以被Fire点燃或扑灭。
// 定义Tree类
public class Tree extends Agent {
private Point position;
private boolean isBurning;
public void initialize(Point position) {
this.position = position;
this.isBurning = false;
}
public boolean isBurning() {
return isBurning;
}
public void setBurning(boolean isBurning) {
this.isBurning = isBurning;
}
public Point getPosition() {
return position;
}
}
// 定义Fire类
public class Fire extends Agent {
private Point position;
private double spreadRate;
public void initialize(Point position, double spreadRate) {
this.position = position;
this.spreadRate = spreadRate;
}
public void spread(List<Tree> trees) {
for (Tree tree : trees) {
double distance = position.distanceTo(tree.getPosition());
if (distance < spreadRate && !tree.isBurning()) {
tree.setBurning(true);
}
}
}
public void onTimer() {
this.spread();
}
}
// 定义主类
public class Main extends Agent {
private List<Tree> trees;
private Fire fire;
public void initialize() {
// 创建100个Tree实例
trees = new ArrayList<>();
for (int i = 0; i < 100; i++) {
Point position = new Point(uniform(0, 100), uniform(0, 100));
Tree tree = new Tree();
tree.initialize(position);
trees.add(tree);
}
// 初始化Fire
fire = new Fire();
fire.initialize(new Point(50, 50), 10);
// 启动仿真
startSimulation();
}
public void startSimulation() {
// 启动Fire的定时器
fire.addEvent(new Event() {
@Override
public void action() {
fire.onTimer();
}
});
// 定期检查树的状态
addEvent(new Event() {
@Override
public void action() {
for (Tree tree : trees) {
if (tree.isBurning()) {
System.out.println("Tree at " + tree.getPosition().toString() + " is burning.");
}
}
}
});
}
}
5. Agent建模的高级技巧
5.1 动态Agent生成
动态Agent生成是指在仿真过程中根据特定条件或事件生成新的Agent。这可以通过定时事件或条件事件来实现。
5.1.1 示例：动态生成新的Car
假设我们有一个模拟交通流量的模型，每分钟生成新的Car实例。
// 定义Car类
public class Car extends Agent {
private Point position;
private double velocity;
private TrafficLight currentTrafficLight;
public void initialize(Point position, double velocity, TrafficLight currentTrafficLight) {
this.position = position;
this.velocity = velocity;
this.currentTrafficLight = currentTrafficLight;
}
public void move() {
if (currentTrafficLight != null && currentTrafficLight.isRed()) {
velocity = 0;
} else {
position = new Point(position.getX() + velocity, position.getY());
}
}
public void onTimer() {
this.move();
}
}
// 定义TrafficLight类
public class TrafficLight extends Agent {
private boolean isRed;
public void initialize(boolean isRed) {
this.isRed = isRed;
}
public boolean isRed() {
return isRed;
}
public void toggleLight() {
isRed = !isRed;
}
public void onTimer() {
if (getEngine().getElapsedTime() % 10 == 0) {
toggleLight();
}
}
}
// 定义主类
public class Main extends Agent {
private List<Car> cars;
private TrafficLight trafficLight;
public void initialize() {
// 初始化交通灯
trafficLight = new TrafficLight();
trafficLight.initialize(true);
// 创建初始的10个Car实例
cars = new ArrayList<>();
for (int i = 0; i < 10; i++) {
Point position = new Point(uniform(0, 100), 0);
double velocity = uniform(1, 5);
Car car = new Car();
car.initialize(position, velocity, trafficLight);
cars.add(car);
}
// 启动仿真
startSimulation();
}
public void startSimulation() {
// 启动交通灯的定时器
trafficLight.addEvent(new Event() {
@Override
public void action() {
trafficLight.onTimer();
}
});
// 启动所有Car的定时器
for (Car car : cars) {
car.addEvent(new Event() {
@Override
public void action() {
car.onTimer();
}
});
}
// 每分钟生成新的Car
addEvent(new Event() {
@Override
public void action() {
Point position = new Point(uniform(0, 100), 0);
double velocity = uniform(1, 5);
Car car = new Car();
car.initialize(position, velocity, trafficLight);
cars.add(car);
}
});
}
}
5.2 Agent的分层建模
分层建模是指将Agent分为不同的层次，每个层次的Agent具有不同的复杂度和功能。这可以提高模型的可读性和可维护性。
5.2.1 示例：分层建模模拟城市交通
假设我们有一个模拟城市交通的模型，包含三个层次的Agent：Driver、Car和TrafficLight。
// 定义Driver类
public class Driver extends Agent {
private Car car;
private List<Point> destinations;
public void initialize(Car car, List<Point> destinations) {
this.car = car;
this.destinations = destinations;
}
public void decideNextDestination() {
Point nextDestination = destinations.get(uniform(0, destinations.size() - 1));
car.setDestination(nextDestination);
}
public void onTimer() {
this.decideNextDestination();
}
}
// 定义Car类
public class Car extends Agent {
private Point position;
private double velocity;
private Point destination;
private TrafficLight currentTrafficLight;
public void initialize(Point position, double velocity, TrafficLight currentTrafficLight) {
this.position = position;
this.velocity = velocity;
this.currentTrafficLight = currentTrafficLight;
}
public void setDestination(Point destination) {
this.destination = destination;
}
public void move() {
if (currentTrafficLight != null && currentTrafficLight.isRed()) {
velocity = 0;
} else {
position = new Point(position.getX() + velocity * (destination.getX() - position.getX()),
position.getY() + velocity * (destination.getY() - position.getY()));
}
}
public void onTimer() {
this.move();
}
}
// 定义TrafficLight类
public class TrafficLight extends Agent {
private boolean isRed;
public void initialize(boolean isRed) {
this.isRed = isRed;
}
public boolean isRed() {
return isRed;
}
public void toggleLight() {
isRed = !isRed;
}
public void onTimer() {
if (getEngine().getElapsedTime() % 10 == 0) {
toggleLight();
}
}
}
// 定义主类
public class Main extends Agent {
private List<Driver> drivers;
private List<Car> cars;
private TrafficLight trafficLight;
public void initialize() {
// 初始化交通灯
trafficLight = new TrafficLight();
trafficLight.initialize(true);
// 创建10个Car实例
cars = new ArrayList<>();
for (int i = 0; i < 10; i++) {
Point position = new Point(uniform(0, 100), 0);
double velocity = uniform(1, 5);
Car car = new Car();
car.initialize(position, velocity, trafficLight);
cars.add(car);
}
// 创建10个Driver实例
drivers = new ArrayList<>();
for (int i = 0; i < 10; i++) {
Car car = cars.get(i);
List<Point> destinations = Arrays.asList(
new Point(50, 50),
new Point(70, 70),
new Point(30, 30)
);
Driver driver = new Driver();
driver.initialize(car, destinations);
drivers.add(driver);
}
// 启动仿真
startSimulation();
}
public void startSimulation() {
// 启动交通灯的定时器
trafficLight.addEvent(new Event() {
@Override
public void action() {
trafficLight.onTimer();
}
});
// 启动所有Car的定时器
for (Car car : cars) {
```java
// 定义主类
public class Main extends Agent {
private List<Driver> drivers;
private List<Car> cars;
private TrafficLight trafficLight;
public void initialize() {
// 初始化交通灯
trafficLight = new TrafficLight();
trafficLight.initialize(true);
// 创建10个Car实例
cars = new ArrayList<>();
for (int i = 0; i < 10; i++) {
Point position = new Point(uniform(0, 100), 0);
double velocity = uniform(1, 5);
Car car = new Car();
car.initialize(position, velocity, trafficLight);
cars.add(car);
}
// 创建10个Driver实例
drivers = new ArrayList<>();
for (int i = 0; i < 10; i++) {
Car car = cars.get(i);
List<Point> destinations = Arrays.asList(
new Point(50, 50),
new Point(70, 70),
new Point(30, 30)
);
Driver driver = new Driver();
driver.initialize(car, destinations);
drivers.add(driver);
}
// 启动仿真
startSimulation();
}
public void startSimulation() {
// 启动交通灯的定时器
trafficLight.addEvent(new Event() {
@Override
public void action() {
trafficLight.onTimer();
}
});
// 启动所有Car的定时器
for (Car car : cars) {
car.addEvent(new Event() {
@Override
public void action() {
car.onTimer();
}
});
}
// 启动所有Driver的定时器
for (Driver driver : drivers) {
driver.addEvent(new Event() {
@Override
public void action() {
driver.onTimer();
}
});
}
}
}
5.3 Agent的状态管理
Agent的状态管理是指在仿真过程中动态地改变Agent的状态。这可以通过状态图、事件和条件语句来实现。状态图是一种可视化工具，用于定义Agent的状态及其转换规则。
5.3.1 示例：使用状态图管理Car的状态
假设我们有一个模拟交通流量的模型，其中Car有三种状态：Moving、Stopped和Arrived。Car的状态转换规则如下：
-
当交通灯是红灯时，Car从
Moving状态转换到Stopped状态。 -
当交通灯变为绿灯时，Car从
Stopped状态转换到Moving状态。 -
当Car到达目标位置时，从
Moving状态转换到Arrived状态。
// 定义Car类
public class Car extends Agent {
private Point position;
private double velocity;
private Point destination;
private TrafficLight currentTrafficLight;
private State state;
public enum State {
MOVING, STOPPED, ARRIVED
}
public void initialize(Point position, double velocity, TrafficLight currentTrafficLight) {
this.position = position;
this.velocity = velocity;
this.currentTrafficLight = currentTrafficLight;
this.state = State.MOVING;
}
public void setDestination(Point destination) {
this.destination = destination;
}
public void move() {
if (state == State.MOVING) {
if (currentTrafficLight != null && currentTrafficLight.isRed()) {
state = State.STOPPED;
velocity = 0;
} else {
position = new Point(position.getX() + velocity * (destination.getX() - position.getX()),
position.getY() + velocity * (destination.getY() - position.getY()));
if (position.distanceTo(destination) < 1) {
state = State.ARRIVED;
}
}
} else if (state == State.STOPPED) {
if (currentTrafficLight != null && !currentTrafficLight.isRed()) {
state = State.MOVING;
velocity = uniform(1, 5);
}
}
}
public void onTimer() {
this.move();
}
}
5.4 Agent的决策规则
Agent的决策规则是指Agent在面对不同情况时的决策逻辑。这些规则可以基于简单的条件语句，也可以使用复杂的算法，如机器学习模型。
5.4.1 示例：基于条件语句的决策规则
假设我们有一个模拟人群疏散的模型，其中Person需要根据周围环境的危险程度来决定是否加快速度或改变方向。
// 定义Person类
public class Person extends Agent {
private double age;
private String gender;
private Point position;
private double velocity;
private Point destination;
public void initialize(double age, String gender, Point position, double velocity, Point destination) {
this.age = age;
this.gender = gender;
this.position = position;
this.velocity = velocity;
this.destination = destination;
}
public void move() {
// 检查周围环境的危险程度
double dangerLevel = checkDangerLevel(position);
if (dangerLevel > 0.5) {
// 如果危险程度高，加快速度
velocity = Math.min(velocity * 1.5, 10);
} else {
// 否则，保持正常速度
position = new Point(position.getX() + velocity * (destination.getX() - position.getX()),
position.getY() + velocity * (destination.getY() - position.getY()));
}
}
private double checkDangerLevel(Point position) {
// 模拟危险程度检测
return uniform(0, 1);
}
public void onTimer() {
this.move();
}
}
5.5 Agent的自适应行为
Agent的自适应行为是指Agent能够根据环境的变化或历史数据调整其行为。这可以通过学习算法或自适应规则来实现。
5.5.1 示例：自适应行为的Agent
假设我们有一个模拟商场顾客的模型，Customer可以根据过去的购物体验选择不同的商店。
// 定义Customer类
public class Customer extends Agent {
private Point position;
private double satisfaction;
private Map<Shop, Double> shopSatisfaction;
public void initialize(Point position, Map<Shop, Double> shopSatisfaction) {
this.position = position;
this.satisfaction = 0.5; // 初始满意度
this.shopSatisfaction = shopSatisfaction;
}
public void chooseShop(List<Shop> shops) {
// 根据过去的满意度选择商店
double maxSatisfaction = 0;
Shop chosenShop = null;
for (Shop shop : shops) {
double satisfaction = shopSatisfaction.getOrDefault(shop, 0.5);
if (satisfaction > maxSatisfaction) {
maxSatisfaction = satisfaction;
chosenShop = shop;
}
}
if (chosenShop != null) {
destination = chosenShop.getPosition();
System.out.println("Customer " + this.getId() + " chose shop " + chosenShop.getId());
}
}
public void move() {
// 移动到目标商店
position = new Point(position.getX() + velocity * (destination.getX() - position.getX()),
position.getY() + velocity * (destination.getY() - position.getY()));
}
public void updateSatisfaction(Shop shop, double newSatisfaction) {
// 更新对特定商店的满意度
shopSatisfaction.put(shop, newSatisfaction);
}
public void onTimer() {
this.chooseShop(shops);
this.move();
}
}
// 定义Shop类
public class Shop extends Agent {
private Point position;
private double serviceQuality;
public void initialize(Point position, double serviceQuality) {
this.position = position;
this.serviceQuality = serviceQuality;
}
public Point getPosition() {
return position;
}
public double getServiceQuality() {
return serviceQuality;
}
}
// 定义主类
public class Main extends Agent {
private List<Customer> customers;
private List<Shop> shops;
public void initialize() {
// 创建10个Shop实例
shops = new ArrayList<>();
for (int i = 0; i < 10; i++) {
Point position = new Point(uniform(0, 100), uniform(0, 100));
double serviceQuality = uniform(0, 1);
Shop shop = new Shop();
shop.initialize(position, serviceQuality);
shops.add(shop);
}
// 创建100个Customer实例
customers = new ArrayList<>();
for (int i = 0; i < 100; i++) {
Point position = new Point(uniform(0, 100), uniform(0, 100));
Map<Shop, Double> shopSatisfaction = new HashMap<>();
for (Shop shop : shops) {
shopSatisfaction.put(shop, uniform(0, 1));
}
Customer customer = new Customer();
customer.initialize(position, shopSatisfaction);
customers.add(customer);
}
// 启动仿真
startSimulation();
}
public void startSimulation() {
// 启动所有Customer的定时器
for (Customer customer : customers) {
customer.addEvent(new Event() {
@Override
public void action() {
customer.onTimer();
}
});
}
// 定期更新顾客的满意度
addEvent(new Event() {
@Override
public void action() {
for (Customer customer : customers) {
if (customer.getPosition().distanceTo(customer.getDestination()) < 1) {
Shop shop = shops.stream()
.filter(s -> s.getPosition().equals(customer.getDestination()))
.findFirst()
.orElse(null);
if (shop != null) {
double newSatisfaction = uniform(shop.getServiceQuality() - 0.1, shop.getServiceQuality() + 0.1);
customer.updateSatisfaction(shop, newSatisfaction);
}
}
}
}
});
}
}
5.6 Agent的集合和群体行为
Agent的集合和群体行为是指多个Agent作为一个整体进行交互和协作。这可以通过集合操作、群体算法或社交网络来实现。
5.6.1 示例：模拟鸟群的群体行为
假设我们有一个模拟鸟群的模型，其中Bird需要根据周围其他鸟的位置和速度来调整自己的飞行方向和速度。
// 定义Bird类
public class Bird extends Agent {
private Point position;
private Point velocity;
private List<Bird> neighbors;
public void initialize(Point position, Point velocity) {
this.position = position;
this.velocity = velocity;
}
public void updateNeighbors(List<Bird> allBirds) {
this.neighbors = allBirds.stream()
.filter(b -> b != this && b.getPosition().distanceTo(this.position) < 20)
.collect(Collectors.toList());
}
public void move() {
if (!neighbors.isEmpty()) {
Point avgPosition = neighbors.stream()
.map(Bird::getPosition)
.reduce(Point::add)
.map(p -> p.scale(1.0 / neighbors.size()))
.orElse(position);
Point avgVelocity = neighbors.stream()
.map(Bird::getVelocity)
.reduce(Point::add)
.map(p -> p.scale(1.0 / neighbors.size()))
.orElse(velocity);
// 调整位置和速度
position = new Point(position.getX() + velocity.getX(), position.getY() + velocity.getY());
velocity = new Point(velocity.getX() + (avgPosition.getX() - position.getX()) * 0.01,
velocity.getY() + (avgPosition.getY() - position.getY()) * 0.01);
} else {
position = new Point(position.getX() + velocity.getX(), position.getY() + velocity.getY());
}
}
public Point getPosition() {
return position;
}
public Point getVelocity() {
return velocity;
}
public void onTimer() {
this.move();
}
}
// 定义主类
public class Main extends Agent {
private List<Bird> birds;
public void initialize() {
// 创建100个Bird实例
birds = new ArrayList<>();
for (int i = 0; i < 100; i++) {
Point position = new Point(uniform(0, 100), uniform(0, 100));
Point velocity = new Point(uniform(-1, 1), uniform(-1, 1));
Bird bird = new Bird();
bird.initialize(position, velocity);
birds.add(bird);
}
// 启动仿真
startSimulation();
}
public void startSimulation() {
// 定期更新每个Bird的邻居和移动
addEvent(new Event() {
@Override
public void action() {
for (Bird bird : birds) {
bird.updateNeighbors(birds);
bird.onTimer();
}
}
});
}
}
6. 总结
Agent建模方法在AnyLogic中提供了强大的工具，用于模拟复杂系统中的个体行为及其相互作用。通过定义Agent的属性、方法和事件，可以构建出高度复杂的仿真模型。此外，动态Agent生成、分层建模、状态管理、决策规则和自适应行为等高级技巧，可以进一步增强模型的复杂性和准确性。希望本文档能帮助你更好地理解和应用Agent建模方法。
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