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CP468 - Artificial Intelligence CHAPTER 4 NOTES CA$13.28   Add to cart

Class notes

CP468 - Artificial Intelligence CHAPTER 4 NOTES

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  • August 21, 2022
  • 9
  • 2021/2022
  • Class notes
  • Sukhjit singh
  • Chapter 2, 3, and 4
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, LOCAL SEARCH
from start state to
Local search
algorithms operate by searching a





neighboring states , without
keeping track of the paths ,
nor the
set of states that have been reached

These algorithms are not systematic [they
might never explore a portion
of the search space where a solution actually resides]
advantages
:
2 key





→ (1) Use
very little memory
→ (2) Often find reasonable solutions in large or infinite state
spaces for which systematic algorithms are unsuitable
Local search
algorithms can also solve optimization problems in which the


,

aim is to find the best state accordingto an objective function

If state corresponds to an objective function , then the aim is to
find the highest peak a maximum and we call the process
global
- -




hill -


climbing

If elevation corresponds to cost then the aim is to find the lowest
,


valley -
a
global minimum and we call it gradient descent
-




HILL CLIMBING
Hill climbing does not look ahead beyond the immediate neighbors of





the current state

start :
whenever

Repeat :
move to the best neighboring state [ heads in the direction that
provides the steepest ascent]

If no
neighbor is better than current
,
quit

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