1. CS1001 Lecture 25

2. Overview Homework 4 Homework 4 Artificial Intelligence Artificial Intelligence Database Systems Database Systems

3. Reading Brookshear, 11 Brookshear, 11 Brookshear, 10 Brookshear, 10 Brookshear, 9 Brookshear, 9

4. Homework 4 Check Courseworks Check Courseworks Problems based on Problems based on –Handout (Smullyan, Natural Deduction) –Question from Ch. 10 –Question from Ch. 11

5. Artificial Intelligence Reasoning (Production Systems) Reasoning (Production Systems) –Goal is to derive a solution given facts and rules Searching Searching –You are given facts and rules and search all possible combinations to find some desired solution (usually minimum/max) Heuristics Heuristics –Operate based on guidelines you know to be true about a problem

6. Paradigms in AI “Top Down” “Top Down” –Describe intelligent behavior as rule sets –Define behavior at the highest level and refine as need be –Examples: most production systems, expert systems “Bottom Up” “Bottom Up” –Define very basic behavior of “agents” –Describe simple rules of how these agents interact –Simulate interactions on a grand scale

7. A Production System

8. Genetic Algorithms A “Bottom Up” approach A “Bottom Up” approach Create simple logic and rules for interactions Create simple logic and rules for interactions Essentially, a GA is a program that writes and alters other programs. It then simulates those programs and evaluates their performance Essentially, a GA is a program that writes and alters other programs. It then simulates those programs and evaluates their performance http://math.hws.edu/xJava/GA/ http://math.hws.edu/xJava/GA/ http://math.hws.edu/xJava/GA/ http://users.ox.ac.uk/~quee0818/ts/ts.html http://users.ox.ac.uk/~quee0818/ts/ts.html http://users.ox.ac.uk/~quee0818/ts/ts.html

9. Expert Systems Expert systems are a strict set of rules Expert systems are a strict set of rules These rules allow for drawing conclusions from an initial set of facts These rules allow for drawing conclusions from an initial set of facts Propositional logic could be used as the mathematical system behind an expert system Propositional logic could be used as the mathematical system behind an expert system Example: If a patient has a Hematocrit reading of 8, he/she has severe Anemia Example: If a patient has a Hematocrit reading of 8, he/she has severe Anemia

10. Neural Networks Neural networks are based on the biological function of brain neurons (sort of) Neural networks are based on the biological function of brain neurons (sort of) This is a learning model, whereby the model can be trained and updated over time This is a learning model, whereby the model can be trained and updated over time

11. Neural Networks

12. Semantic Networks

13. Blackboard Systems Blackboard systems contain all sorts of subsystems that we’ve seen so far Blackboard systems contain all sorts of subsystems that we’ve seen so far They are a metaphorical area for different AI systems to exchange predictions and vote on a consensus as a whole They are a metaphorical area for different AI systems to exchange predictions and vote on a consensus as a whole