无人车准备0902

In general, entropy measures the amount of uncertainty. Since the update step increases uncertainty, then entropy should increase. The measurement step decreases uncertainty, so entropy should decrease.

Let's look at our current example where the robot could be at five different positions. The maximum uncertainty occurs when all positions have equal probabilities $[0.2,0.2,0.2,0.2,0.2]$

Following the formula (, we get −.$Entropy=\mathrm{\Sigma }(-p\times log(p))$, we get $-5\times (.2)\times log(0.2)=0.699$.

Taking a measurement should decrease uncertainty and thus decrease entropy. Let's say after taking a measurement, the probabilities become $[0.05,0.05,0.05,0.8,0.05]$.  Now the entropy decreased to 0.338. Hence a measurement step should decrease entropy whereas an update step should increase entropy.

关于str.translate(table[,deletechars])

[python] view plain copy

1. import string    
2.     
3. s = 'abcd--dcba'    
4.     
5. # 参数from和to的长度必须一致    
6. table = string.maketrans('', '')   # type(table) is 'str'  
7. print(s.translate(table))   # 输出 abcd--dcba  
8.   
9. table = string.maketrans('ab', '12')  
10. print(s.translate(table))   # 输出 12cd--dc21  
11.   
12. # 将先删除'ad'，然后再转换  
13. print(s.translate(table, 'ad'))     # 输出 2c--c2