目标堆栈规划是一种简单高效的人工智能规划算法，用于解决复合目标问题。它的工作原理是**将总体目标分解为更小的子目标，然后以向后的顺序逐一解决它们。
让我们考虑一个简单的例子来说明目标堆栈规划。想象一下你想要烤一个蛋糕，目标是准备一个美味的蛋糕。为了实现这个目标，您需要执行子目标，例如准备面糊、预热烤箱、烘烤蛋糕和装饰。
- 准备面糊
- 预热烤箱
- 烤蛋糕
- 装饰蛋糕
这些子目标中的每一个都可能需要进一步分解为更细粒度的行动。例如，准备面糊可能涉及收集原料、混合它们以及将面糊倒入烤盘等步骤。这些步骤将继续分解为更简单的操作，直到我们达到每个操作都可以直接执行的级别。再想象一下，水槽里有一堆脏盘子。您的总体目标是拥有一个干净的厨房。使用目标堆栈规划，您将：
- 将主要目标“清洁厨房”推入堆栈。
- 将主要目标分解为子目标，例如“洗碗”、“擦干碗”和“把碗收起来”。
- 按照需要完成的顺序将这些子目标推入堆栈（先清洗后干燥等）。
- 将最上面的子目标从堆栈中弹出并专注于实现它（例如，洗碗）。
- 实现子目标后，将其从堆栈中弹出并继续下一个目标（擦干盘子）。
- 重复步骤 4-5，直到实现所有子目标并达到主要目标（“清洁厨房”）。
规划过程通常涉及以下步骤：
- 目标分解：将初始目标分解为子目标。这种分解一直持续到达到原始动作为止。
- 堆栈操作：堆栈用于管理目标和子目标。当需要实现目标时，将目标压入堆栈；当实现目标或需要关注计划的不同分支时，将目标从堆栈中弹出。
- 计划执行：系统执行行动以实现目标。当每个子目标实现时，相应的目标就会从堆栈中弹出。
- 回溯：如果系统遇到障碍或无法实现子目标，它可能会回溯到之前的状态并尝试替代计划。
目标堆栈规划在实现目标的顺序很重要并且目标可以分层分解的领域特别有用。它提供了一种模仿人类解决问题策略的结构化规划方法。
目标堆栈规划的优点：
- 简单易懂：将目标分解为更小的步骤的基本概念直观且易于掌握。
- 对某些问题有效：对于具有明确定义和有序子目标的问题，目标堆栈规划可以是寻找解决方案的非常有效的方法。
- 灵活：可以通过调整目标分解方式来适应不同类型的问题。
目标堆栈规划的缺点：
- 不适用于所有问题：对于具有复杂或相互依赖的子目标的问题可能会变得低效或不切实际。
- 可能找不到最佳解决方案：专注于按特定顺序实现目标，这可能并不总能带来最有效或最佳的解决方案。
- 有限的规划期限：最适合具有明确目标的短期规划。
Java代码
import java.util.Stack;
class Goal {
String description;
Goal(String description) {
this.description = description;
}
}
public class GoalStackPlanning {
public static void main(String[] args) {
Stack<Goal> goalStack = new Stack<>();
// Define the high-level goal
Goal initialGoal = new Goal("Have a delicious cake ready")
// Push the high-level goal onto the stack
goalStack.push(initialGoal);
// Start planning
while (!goalStack.isEmpty()) {
Goal currentGoal = goalStack.pop();
System.out.println("Current Goal: " + currentGoal.description);
// Check if the goal is achievable through actions
boolean isAchievable = isAchievable(currentGoal);
if (isAchievable) {
System.out.println("Goal achieved: " + currentGoal.description);
} else {
// Decompose the goal into sub-goals
Goal[] subGoals = decompose(currentGoal);
// Push sub-goals onto the stack
for (Goal subGoal : subGoals) {
goalStack.push(subGoal);
}
}
}
}
// Function to check if a goal is achievable through actions
static boolean isAchievable(Goal goal) {
// 在实际执行过程中，我们会对照一系列规则和条件
// 以确定目标是否可以直接实现。
// 为简单起见，我们假设所有目标都可以直接实现。
return true;
}
// Function to decompose a goal into sub-goals
static Goal[] decompose(Goal goal) {
// 在实际执行中，我们会定义分解规则，将 // 目标分解为多个子目标。
// 目标分解成子目标。
// 为了简单起见，我们将暂时返回一个空数组。
return new Goal[0];
}
}
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在这个示例中，我们有一个 Goal 类来表示每个目标，还有一个 Stack 来维护目标堆栈。GoalStackPlanning 类中的主循环会从堆栈中弹出目标，并检查它们是否可实现。如果目标可实现，则打印出目标已实现。否则，它会将目标分解为多个子目标（为简单起见，分解规则未执行）。
由于高级目标是可实现的，因此程序无需进行任何分解就能直接实现该目标。
实现目标分解
现在，为了让程序更有用，让我们来实现目标分解规则。我们将修改 decompose 函数，把高层目标分解为子目标。
import java.util.Stack;
class Goal {
String description;
Goal(String description) {
this.description = description;
}
}
public class GoalStackPlanning {
public static void main(String[] args) {
Stack<Goal> goalStack = new Stack<>();
// Define the high-level goal
Goal initialGoal = new Goal("Have a delicious cake ready");
// Push the high-level goal onto the stack
goalStack.push(initialGoal);
// Start planning
while (!goalStack.isEmpty()) {
Goal currentGoal = goalStack.pop();
System.out.println("Current Goal: " + currentGoal.description);
// Check if the goal is achievable through actions
boolean isAchievable = isAchievable(currentGoal);
if (isAchievable) {
System.out.println("Goal achieved: " + currentGoal.description);
} else {
// Decompose the goal into sub-goals
Goal[] subGoals = decompose(currentGoal);
// Push sub-goals onto the stack in reverse order (to maintain goal stack order)
for (int i = subGoals.length - 1; i >= 0; i--) {
goalStack.push(subGoals[i]);
}
}
}
}
// Function to check if a goal is achievable through actions
static boolean isAchievable(Goal goal) {
// 在实际执行过程中，我们会对照一系列规则和条件
// 以确定目标是否可以直接实现。
// 为简单起见，我们假设所有目标都可以直接实现。
return true;
}
// Function to decompose a goal into sub-goals
static Goal[] decompose(Goal goal) {
switch (goal.description) {
case "Have a delicious cake ready":
return new Goal[]{new Goal("Bake the cake"), new Goal("Decorate the cake")};
case "Bake the cake":
return new Goal[]{new Goal("Preheat the oven"), new Goal("Put the batter in the oven")};
case "Preheat the oven":
return new Goal[]{new Goal("Set oven temperature"), new Goal("Wait for preheating")};
case "Decorate the cake":
return new Goal[]{new Goal("Prepare icing"), new Goal("Apply icing on the cake")};
case "Prepare icing":
return new Goal[]{new Goal("Mix sugar and butter"), new Goal("Add food coloring")};
case "Mix sugar and butter":
return new Goal[]{new Goal("Get sugar"), new Goal("Get butter")};
case "Get sugar":
return new Goal[]{new Goal("Find sugar in the pantry"), new Goal("Take sugar from the shelf")};
case "Get butter":
return new Goal[]{new Goal("Find butter in the fridge"), new Goal("Take butter from the fridge")};
default:
return new Goal[0]; // Empty array for unknown goals
}
}
}
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输出：
Current Goal: Have a delicious cake ready
Current Goal: Decorate the cake
Current Goal: Apply icing on the cake
Goal achieved: Apply icing on the cake
Current Goal: Prepare icing
Current Goal: Add food coloring
Goal achieved: Add food coloring
Current Goal: Mix sugar and butter
Current Goal: Get butter
Current Goal: Find butter in the fridge
Goal achieved: Find butter in the fridge
Current Goal: Take butter from the fridge
Goal achieved: Take butter from the fridge
Goal achieved: Get butter
Current Goal: Get sugar
Current Goal: Find sugar in the pantry
Goal achieved: Find sugar in the pantry
Current Goal: Take sugar from the shelf
Goal achieved: Take sugar from the shelf
Goal achieved: Get sugar
Goal achieved: Mix sugar and butter
Goal achieved: Prepare icing
Goal achieved: Decorate the cake
Current Goal: Bake the cake
Current Goal: Put the batter in the oven
Current Goal: Prepare the batter
Current Goal: Mix the ingredients
Current Goal: Add sugar
Goal achieved: Add sugar
Current Goal: Mix flour and eggs
Goal achieved: Mix flour and eggs
Goal achieved: Mix the ingredients
Goal achieved: Prepare the batter
Current Goal: Preheat the oven
Current Goal: Wait for preheating
Goal achieved: Wait for preheating
Current Goal: Set oven temperature
Goal achieved: Set oven temperature
Goal achieved: Preheat the oven
Goal achieved: Bake the cake
Goal achieved: Have a delicious cake ready
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从输出结果中我们可以看到，程序成功地将高层目标分解为多个子目标，并实现了每个子目标，最终实现了 "准备好美味蛋糕 "这一高层目标。
使用fork-join实现目标规划
使用 Java Fork-Join 实现目标堆栈规划需要定义一个规划器，该规划器可以并行和并发的方式处理目标和操作的执行。
下面是一个简化示例，说明如何使用 Java Fork-Join 构建基本的目标堆栈规划器。该示例假定有一个包含子目标和操作的单一目标。
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.RecursiveTask;
import java.util.concurrent.ForkJoinPool;
class Goal {
String description;
List<Object> subgoalsOrActions;
Goal(String description, List<Object> subgoalsOrActions) {
this.description = description;
this.subgoalsOrActions = subgoalsOrActions;
}
}
class GoalStackPlanner extends RecursiveTask<Void> {
Goal goal;
GoalStackPlanner(Goal goal) {
this.goal = goal;
}
@Override
protected Void compute() {
if (goal.subgoalsOrActions.isEmpty()) {
executeAction(goal);
} else {
List<RecursiveTask<Void>> subtasks = new ArrayList<>();
for (Object subgoalOrAction : goal.subgoalsOrActions) {
if (subgoalOrAction instanceof Goal) {
Goal subgoal = (Goal) subgoalOrAction;
subtasks.add(new GoalStackPlanner(subgoal).fork());
} else if (subgoalOrAction instanceof Action) {
Action action = (Action) subgoalOrAction;
subtasks.add(new ActionTask(action).fork());
}
}
for (RecursiveTask<Void> subtask : subtasks) {
subtask.join();
}
}
return null;
}
private void executeAction(Goal goal) {
System.out.println("Executing action for goal: " + goal.description);
}
}
class Action {
String description;
Action(String description) {
this.description = description;
}
void execute() {
System.out.println("Executing action: " + description);
}
}
class ActionTask extends RecursiveTask<Void> {
private Action action;
ActionTask(Action action) {
this.action = action;
}
@Override
protected Void compute() {
action.execute();
return null;
}
}
public class Main {
public static void main(String[] args) {
List<Object> subgoalsOrActions = new ArrayList<>();
subgoalsOrActions.add(new Goal("Subgoal 1", List.of(new Action("Action 1"))));
subgoalsOrActions.add(new Action("Action 2"));
Goal topGoal = new Goal("Top-level goal", subgoalsOrActions);
ForkJoinPool.commonPool().invoke(new GoalStackPlanner(topGoal));
}
}
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在本例中，GoalStackPlanner 类扩展了 RecursiveTask<Void>，其计算方法负责处理目标和操作的执行。ActionTask 类用于并行执行单个操作。main 方法创建一个顶级目标，并使用 Fork-Join 框架调用 GoalStackPlanner。
这是一个简化的示例，在现实世界中，您需要实现更复杂的目标分解、处理状态、错误恢复，并可能根据应用程序的具体情况引入额外的并发控制机制。
Python代码实现
Python 中的目标堆栈规划（Goal Stack Planning）涉及实现一个系统，在这个系统中，目标被分解成子目标和操作，然后执行这些子目标和操作来实现总体目标。下面是 Python 中的一个简单示例，用于说明目标堆栈规划器的基本结构：
class Goal:
def __init__(self, description, subgoals_or_actions=None):
self.description = description
self.subgoals_or_actions = subgoals_or_actions or []
class Action:
def __init__(self, description):
self.description = description
def execute(self):
print("Executing action:", self.description)
class GoalStackPlanner:
def __init__(self):
self.stack = []
def execute_goal(self, goal):
print("Executing goal:", goal.description)
for subgoal_or_action in goal.subgoals_or_actions:
if isinstance(subgoal_or_action, Goal):
self.stack.append(subgoal_or_action)
elif isinstance(subgoal_or_action, Action):
subgoal_or_action.execute()
def plan(self, top_level_goal):
self.stack.append(top_level_goal)
while self.stack:
current_goal = self.stack.pop()
self.execute_goal(current_goal)
# Example usage
if __name__ == "__main__":
action1 = Action("Action 1")
action2 = Action("Action 2")
subgoal1 = Goal("Subgoal 1", [action1])
subgoal2 = Goal("Subgoal 2", [action2])
top_level_goal = Goal("Top-level goal", [subgoal1, subgoal2])
planner = GoalStackPlanner()
planner.plan(top_level_goal)
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在这个示例中，
- Goal 类代表一个目标，包含一个描述和一个子目标或操作列表。操作类代表一个操作，带有说明和执行方法。
- GoalStackPlanner 类有一个 plan 方法，该方法接收顶层目标并使用目标堆栈执行该目标。
- execute_goal方法负责通过将子目标推送到堆栈或直接执行动作来执行目标。
请记住，这只是一个简化的示例，在实际应用中，您可能需要根据应用程序的具体要求，实施更高级的目标分解、状态处理和错误恢复机制。