Search Algorithms
Tutorial Slides by Andrew Moore
What is a search algorithm? What job does it do and where can it be applied?
1 Classes of search algorithms
1.1 For explicitly stored databases
1.2 For virtual search spaces
1.3 For sub-structures of a given structure
1.4 For quantum computers ...
1 Search Algorithms
A wide collection of search algorithms techniques are discussed in detail by Korf (1996) as a unique method in AI of solving involved problems that require trial and error.
The search algorithm
The above example is completely instructive in this regard.
The search algorithm
The Viterbi algorithm takes an HMM model and an output sequence, [C\, E2, - - - , Cn],
and returns the most probable path through the HMM that outputs the sequence. It also returns
the probability for the path ...
Minimax Search Algorithm
The standard algorithm for two-player perfect-information games such as chess, checkers or othello is minimax search with heuristic static evaluation.
Many search algorithms rapidly increase the memory usage as the problem gets more complex. The agents that were used to simulate the ants have only a relative limited memory and thereby the system is not much affected by the complexity of the problem.
"Naive" search algorithms, such as breadth first search, depth first search and general state space search.[79]
Heuristic or "informed" search.
Combinatorial search algorithms are normally implemented in an efficient imperative programming language, in an expressive declarative programming language such as Prolog, or some compromise, ...
The breadth first search algorithm visits the nodes of the tree along its
breadth, starting from the level with depth 0 to the maximum depth. It can be
easily realized with a queue. For instance, consider the tree, given in figure.
2 The Best-First Search Algorithm 133
4.3 Admissibility, Monotonicity, and Informedness 145
4.4 Using Heuristics in Games 150
4.5 Complexity Issues 157
4.6 Epilogue and References 161
4.7 Exercises 162
5 STOCHASTIC METHODS 165
5.
The Greedy Best-First-Search algorithm works in a similar way, except that it has some estimate (called a heuristic) of how far from the goal any vertex is.
This algorithm, due to Mitchell (1974b), is probably the best known and most widely used optimal design search algorithm.
"Google's patented and powerful search algorithm, PageRank, may mimic the way the human brain retrieves information. ... It seems it might.
Search algorithms used in machine learning which involve iteratively generating new candidate solutions by combining two high scoring earlier (or parent) solutions in a search for a better solution.
Moore, Alexander Gray and Ke Yang (PDF): k-NN search algorithm using Locally sensitive hashing
A Fast Algorithm for Finding k-Nearest Neighbors with Non-metric Dissimilarity by Bin Zhang and Sargur N. Srihari ...
Problem-solving through Search: forward and backward, state-space, blind, heuristic, problem-reduction, A, A*, AO*, minimax, constraint propagation, neural, stochastic, and evolutionary search algorithms, sample applications.
It may look toward new kinds of computers ("parallel" or "fuzzy" or "associative" or whatever) or it may look toward extensions of deductive generality, or information retrieval, or search algorithms-things like better "resolution" methods, ...
 See also: Artificial intelligence, Knowledge, Neural network, Genetic algorithm, AI
  
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