55:) algorithms are state space search algorithms. These are search algorithms in which the search space is a subset of the state space: Each node corresponds to a state of the world, each arc corresponds to a state transition, and the current plan corresponds to the current path in the search space.
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is a collective term for all the data to be searched. Similarly, artificial intelligence programs often employ a process of searching through a finite universe of possible procedures for reaching a goal, to find a procedure or the best procedure to achieve the goal. The universe of possible
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P = the empty plan loop if s satisfies g then return P applicable = {a | a is a ground instance of an operator in O,and precond(a) is true in s} if applicable = ∅ then return failure nondeterministically choose an action a from applicable s = γ(s, a) P = P.a
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P = the empty plan loop if s satisfies g then return P relevant = {a | a is a ground instance of an operator in O that is relevant for g} if relevant = ∅ then return failure nondeterministically choose an action a from relevant P = a.P s = γ(s, a)
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Backward-search is an algorithm that begins with goal state and back track to its initial state. This method is sometimes called "back propagation."
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Forward search is an algorithm that searches forward from the initial state of the world to try to find a state that satisfies the goal formula.
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