Announcements

1. Announcements • Homework 1 due today – write up on The Thinking Machine • Department Picnic: Thursday, September 13 – 1:20 to 2:30 • Lab 0 due Thursday, September 13 • Writing Assignments Posted • Caves of Steel due 10/4 • Current Events Presentation CS 484 – Artificial Intelligence

2. Representations: Semantic Nets, Frames, and Trees Lecture 3

3. The Need for a Good Representation • A computer needs a representation of a problem in order to solve it. • A representation must be: • Efficient – not wasteful in time or resources. • Useful – allows the computer to solve the problem. • Meaningful – really relates to the problem. CS 484 – Artificial Intelligence

4. Semantic Nets • A graph with nodes, connected by edges. • The nodes represent objects or properties. • The edges represent relationships between the objects. • Label to indicate nature of relationship CS 484 – Artificial Intelligence

5. A Simple Semantic Net CS 484 – Artificial Intelligence

6. Create a Semantic Net A Ford is a type of car. Bob owns two cars. Bob parks his car at home. His house is in California, which is a state. Sacramento is the state capital of California. Cars drive on the freeway, such as Route 101 and Highway 81. CS 484 – Artificial Intelligence

7. Your Semantic Web CS 484 – Artificial Intelligence

8. Inheritance • Inheritance is the process by which a subclass inherits properties from a superclass. • Example: • Mammals give birth to live young. • Fido is a mammal. • Therefore Fido gives birth to live young. • In some cases, as in the example above, inherited values may need to be overridden. (Fido may be a mammal, but if he’s male then he probably won’t give birth). CS 484 – Artificial Intelligence

9. Frames • A frame system consists of a number of frames, connected by edges, like a semantic net. • Class frames describe classes. • Instance frames describe instances. • Each frame has a number of slots. • Each slot can be assigned a slot value. CS 484 – Artificial Intelligence

10. Frames: A Simple Example CS 484 – Artificial Intelligence

11. Other relationships • Aggregation – one object being part of another object • Fido has a tail • Association – explains how objects are related to each other • "chases relationship" – how Fido and Fang are related CS 484 – Artificial Intelligence

12. Create a frame-based representation A Ford is a type of car. Bob owns two cars. Bob parks his car at home. His house is in California, which is a state. Sacramento is the state capital of California. Cars drive on the freeway, such as Route 101 and Highway 81. CS 484 – Artificial Intelligence

13. Your Frame-Based Representation CS 484 – Artificial Intelligence

14. Why Are Frames Useful? • Used as a data structure by Expert Systems • All information about an object stored in one place • As opposed to rule-based systems • In real world systems frames have a large number of slots • Searching for all relevant information would take a long time CS 484 – Artificial Intelligence

15. Search Space • A set of possible choices in a given problem • One or more are the solution to the problem • Identify one or more goals • Identify one or more paths to those goals • Problem • set of states • states connected by paths that represent actions CS 484 – Artificial Intelligence

16. Search Trees • Semantic trees – a type of semantic net. • Used to represent search spaces. • Root node has no predecessor. • Leaf nodes have no successors. • Goal nodes (of which there may be more than one) represent solutions to a problem. CS 484 – Artificial Intelligence

17. Search Trees: An Example • A is the root node. • L is the goal node. • H, I, J, K, M, N and O are leaf nodes. • There is only one complete path: • A, C, F, L CS 484 – Artificial Intelligence

18. Example: Missionaries and Cannibals • Three missionaries and three cannibals • Want to cross a river using one canoe. • Canoe can hold up to two people. • Can never be more cannibals than missionaries on either side of the river. • Aim: To get all safely across the river without any missionaries being eaten. CS 484 – Artificial Intelligence

19. A Representation • The first step in solving the problem is to choose a suitable representation. • We will show number of cannibals, missionaries and canoes on each side of the river. • Start state is therefore: • C=3,M=3,B=1 0,0,0 CS 484 – Artificial Intelligence

20. A Simpler Representation • In fact, since the system is closed, we only need to represent one side of the river, as we can deduce the other side. • We will represent the finishing side of the river, and omit the starting side. • So start state is: • 0,0,0 CS 484 – Artificial Intelligence

21. Operators • Now we have to choose suitable operators that can be applied: • Move one cannibal across the river. • Move two cannibals across the river. • Move one missionary across the river. • Move two missionaries across the river. • Move one missionary and one cannibal. CS 484 – Artificial Intelligence

22. The Search Tree • Cycles have been removed. • Nodes represent states, edges represent operators. • There are two shortest paths that lead to the solution. CS 484 – Artificial Intelligence

23. What Other Representations are Possible? CS 484 – Artificial Intelligence

24. Combinatorial Explosion • Problems that involve assigning values to a set of variables can grow exponentially with the number of variables. • Some such problems can be extremely hard to solve (NP-Complete, NP-Hard). • Reduce state space • select good representation help • using heuristics (see chapter 4). CS 484 – Artificial Intelligence

25. Problem Reduction • Breaking a problem down into smaller sub-problems (or sub-goals). • Can be represented using goal trees (or and-or trees). • Nodes in the tree represent sub-problems. • The root node represents the overall problem. • Some nodes are and nodes, meaning all their children must be solved. CS 484 – Artificial Intelligence

26. Problem Reduction: Example CS 484 – Artificial Intelligence