Solving problems by searching. Chapter 3. Why Search?. To achieve goals or to maximize our utility we need to predict what the result of our actions in the future will be. There are many sequences of actions, each with their own utility. We want to find, or search for, the best one.
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Previous problem was static: no attention to changes in environment
Previous problem was observable: it knew its initial state.
Previous problem was deterministic: no new percepts
were necessary, we can predict the future perfectly
Previous problem was discrete: we can enumerate all possibilities
A problem is defined by four items:
initial state e.g., "at Arad“
actions or successor functionS(x) = set of action–state pairs
e.g., x = "at Bucharest”, Checkmate(x)
path cost (additive)
A solution is a sequence of actions leading from the initial state to a goal state
state space must be abstracted for problem solving
-or arrangements of n<=8 queens in leftmost n
columns, 1 per column, such that no queen
attacks any other.
-or add queen to leftmost emptysquare such that it is not attacked by other queens.
[Note: optimal solution of n-Puzzle family is NP-hard]