p1208_TheBlocksProblem模拟

本文介绍了一种简单的方块世界模型,机器人通过特定指令来移动和堆叠方块。包括move、pile等命令,实现对多个方块的操作,并最终输出方块的最终状态。
The Blocks Problem
Time Limit: 1000MSMemory Limit: 10000K
Total Submissions: 1672Accepted: 552

Description

Many areas of Computer Science use simple, abstract domains for both analytical and empirical studies. For example, an early AI study of planning and robotics (STRIPS) used a block world in which a robot arm performed tasks involving the manipulation of blocks.
In this problem you will model a simple block world under certain rules and constraints. Rather than determine how to achieve a specified state, you will "program" a robotic arm to respond to a limited set of commands.
The problem is to parse a series of commands that instruct a robot arm in how to manipulate blocks that lie on a flat table. Initially there are n blocks on the table (numbered from 0 to n-1) with block bi adjacent to block bi+1 for all 0 <= i < n-1 as shown in the diagram below:

The valid commands for the robot arm that manipulates blocks are:

move a onto b
where a and b are block numbers, puts block a onto block b after returning any blocks that are stacked on top of blocks a and b to their initial positions.


move a over b
where a and b are block numbers, puts block a onto the top of the stack containing block b, after returning any blocks that are stacked on top of block a to their initial positions.


pile a onto b
where a and b are block numbers, moves the pile of blocks consisting of block a, and any blocks that are stacked above block a, onto block b. All blocks on top of block b are moved to their initial positions prior to the pile taking place. The blocks stacked above block a retain their order when moved.


pile a over b
where a and b are block numbers, puts the pile of blocks consisting of block a, and any blocks that are stacked above block a, onto the top of the stack containing block b. The blocks stacked above block a retain their original order when moved.


quit
terminates manipulations in the block world.

Any command in which a = b or in which a and b are in the same stack of blocks is an illegal command. All illegal commands should be ignored and should have no affect on the configuration of blocks.

Input

The input begins with an integer n on a line by itself representing the number of blocks in the block world. You may assume that 0 < n < 25.
The number of blocks is followed by a sequence of block commands, one command per line. Your program should process all commands until the quit command is encountered.

You may assume that all commands will be of the form specified above. There will be no syntactically incorrect commands.

Output

The output should consist of the final state of the blocks world. Each original block position numbered i ( 0 <= i < n where n is the number of blocks) should appear followed immediately by a colon. If there is at least a block on it, the colon must be followed by one space, followed by a list of blocks that appear stacked in that position with each block number separated from other block numbers by a space. Don't put any trailing spaces on a line.

There should be one line of output for each block position (i.e., n lines of output where n is the integer on the first line of input).

Sample Input

10
move 9 onto 1
move 8 over 1
move 7 over 1
move 6 over 1
pile 8 over 6
pile 8 over 5
move 2 over 1
move 4 over 9
quit

Sample Output

0: 0
1: 1 9 2 4
2:
3: 3
4:
5: 5 8 7 6
6:
7:
8:
9:

Source

敲了半个多小时 换了种方法,敲了40分钟,调了40分钟,调了20分钟。fine!不要moji~
先展示下效果 https://pan.quark.cn/s/a4b39357ea24 遗传算法 - 简书 遗传算法的理论是根据达尔文进化论而设计出来的算法: 人类是朝着好的方向(最优解)进化,进化过程中,会自动选择优良基因,淘汰劣等基因。 遗传算法(英语:genetic algorithm (GA) )是计算数学中用于解决最佳化的搜索算法,是进化算法的一种。 进化算法最初是借鉴了进化生物学中的一些现象而发展起来的,这些现象包括遗传、突变、自然选择、杂交等。 搜索算法的共同特征为: 首先组成一组候选解 依据某些适应性条件测算这些候选解的适应度 根据适应度保留某些候选解,放弃其他候选解 对保留的候选解进行某些操作,生成新的候选解 遗传算法流程 遗传算法的一般步骤 my_fitness函数 评估每条染色体所对应个体的适应度 升序排列适应度评估值,选出 前 parent_number 个 个体作为 待选 parent 种群(适应度函数的值越小越好) 从 待选 parent 种群 中随机选择 2 个个体作为父方和母方。 抽取父母双方的染色体,进行交叉,产生 2 个子代。 (交叉概率) 对子代(parent + 生成的 child)的染色体进行变异。 (变异概率) 重复3,4,5步骤,直到新种群(parentnumber + childnumber)的产生。 循环以上步骤直至找到满意的解。 名词解释 交叉概率:两个个体进行交配的概率。 例如,交配概率为0.8,则80%的“夫妻”会生育后代。 变异概率:所有的基因中发生变异的占总体的比例。 GA函数 适应度函数 适应度函数由解决的问题决定。 举一个平方和的例子。 简单的平方和问题 求函数的最小值,其中每个变量的取值区间都是 [-1, ...
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