Artificial Intelligence

# Artificial Intelligence

## Artificial Intelligence

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##### Presentation Transcript

1. Artificial Intelligence Tarik Booker

2. What we will cover… • History • Artificial Intelligence as Representation and Search • Languages used in Artificial Intelligence • Applications

3. History of Artificial Intelligence • Derives from Logic • Aristotle • Charles Babbage • George Boole • Alan Turing • Turing Test

4. AI as Representation and Search • Predicate Calculus • State Space • Heuristic Search

5. Predicate Calculus • Covered later in presentation (Logic Programming) • Basics: • Proposition – statement that may or may not be true

6. State Space • The structure of the state that you are in • A four-tuple [N, A, S, GD] • Where: • N is the set of nodes (or states) of the graph • A is the set of arcs (links) between nodes • S, a non-empty subset of N, contains the start state(s) of the problem • GD, a non-empty subset of N contains the goal state(s) of the problem • A solution path is a path through this graph from a node S to a node in GD

7. Heuristics • (From Greek “eurisco” meaning “to discover”) • A strategy for selectively searching a problem space • Searches along lines that have a high probability of success • Not guaranteed to find correct solution

8. Why use Heuristics? • Problem may not have an exact solution because of ambiguities • Ex: Medical Diagnosis • Problem may have exact solution, but the computational cost of finding it may be prohibitive • Ex: Chess • Heuristics are at the core of AI.

9. Heuristic Algorithms • Heuristic Measure • Best-first Search • Tic-Tac Toe (on board)

10. Heuristics Terms • Admissibility • Heuristics that find the shortest path to a goal whenever it exists are said to be admissible • Informedness • Are any heuristics better that the one we are using? • Monotonicity • When a state is discovered using heuristic search, is there a guarantee that the same state won’t be reached with a cheaper cost?

11. Languages Used in AI • LISP • PROLOG

12. Applications of AI • Game Playing • Heuristics • Automated Reasoning and Theorem Proving • Expert Systems • Natural Language Understanding • Planning and Robotics • Machine Learning

13. Sources Luger, George F. Stubblefield, William A. Artificial Intelligence (3rd Edition)