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Tutorial 2-Search Algorithm
Breadth-first search宽度优先搜索
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open表由queue队列实现，因此加在尾部。
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Depth-first search深度优先搜索
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open表由stack栈实现，因此加在头部。
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Hill climbing (a heuristic search algorithm)
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Hill climbing algorithm goes uphill along the steepest possible path until can go no further up, which may return a state that is a local maximum.
Advantages

• Avoid traversal避免遍历所有解。
• Achieve the purpose of improving efficiency提高搜索效率。
  Disadvantages
• Not necesssarily find the global maximum but converge on a local maximum不一定找到最优解但收敛于局部最优解。
• In plateau cases, the hill climber may not be able to determine in which direction it should step, and may wander in a direction that never leads to improvement.在高原(比较平坦)的情况下，登山者可能无法确定应该朝哪个方向前进，并且可能在一个永远无法改善的方向上徘徊。
• Ridges problem: If the target function creates a narrow ridge that ascends in a non-axis-aligned direction, then the hill climber can only ascend the ridge by zig-zagging.山脊问题:如果目标函数创建了一个狭窄的山脊，它以非轴线对齐的方向上升，那么爬山者只能通过曲折攀登山脊。

Best-first Search (Greedy Search贪心算法)
The node with the lowest evaluation is expanded first, i.e., 𝑎𝑟𝑔𝑚𝑖𝑛(𝑓(𝑛))
f(n) = ℎ(𝑛) = 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑐𝑜𝑠𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑐ℎ𝑒𝑎𝑝𝑒𝑠𝑡 𝑝𝑎𝑡ℎ 𝑓𝑟𝑜𝑚 𝑠𝑡𝑎𝑡𝑒 𝑎𝑡 𝑛𝑜𝑑𝑒 𝑛 𝑡𝑜 𝑎 𝑔𝑜𝑎𝑙 𝑠𝑡𝑎𝑡𝑒
If 𝑛 is a goal node, then ℎ(𝑛) = 0.
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Limitations of Greedy Search

1. not optimal
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   A* Search
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   Exercise
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   Breadth-first search：A B C D E F
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   Depth-first search：A D F
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   openList, closeList = [start], []
   while True:
   currentNode = lowest f cost in openList
   if currentNode == end: return
   for neighbour in currentNode.Neighbours:
   if closeList.contains(neighbour) continue
   if new_neighbour_f <= old_neighbour_f or not openList.contains(neighbour):
   neighbour.f = new_neighbour_f
   if not openList.contains(neighbour):
   openList.add(neighbour)
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Tutorial 3-Genetic Algorithm
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Tutorial 4-Multi-objective Optimization
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Exercise 1同 Tutorial 3的Exercise 4
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Tutorial 5-Regression and Gradient Descent
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Tutorial 6-Scaling, Overfitting and Kmeans
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Tutorial 7-Building a Perceptron
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Tutorial 8-Building a Neural Network
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Tutorial 9-Attention and Transformer
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Tutorial 10-Ensemble Learning
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Tutorial 11-Fuzzy
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Tutorial 12-Fuzzy2
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按列两两求最小，然后整列求最大。
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P的行，与Q的列逐个元素求最小值，然后选择最小值里的最大值。
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期中考：

1. 图搜索 * 2
2. 逻辑代数 * 2
3. bfs dfs
4. a*
5. 贝叶斯公式
6. Kmeans
7. 反向传播