1. Artificial Intelligence Techniques Introduction to Artificial Intelligence

2. Artificial Intelligence AI is often divided into two basic ‘camps’ Rule-based systems (RBS) Biological inspired, such as Artificial neural networks (ANN) There are also search methods which some people include. Increasingly hybridisation.

3. In the module Search methods Evolutionary algorithm Neural networks Fuzzy Logic Planning

4. Examples Focus of the applications is the early part of the module is on: Games Robotics Engineering and medicine

5. Assessment Two assignments mini-projects Applying AI to tasks Early part in Java

6. Multi-layered perceptron (Taken from Picton 2004) Input layer Hidden layer Output layer

7. The Ingredients( Taken from: EvoNet Flying Circus www2.cs.uh.edu/~ceick/ai/EC1.ppt ) t t + 1 mutation recombination reproduction selection

8. Data Structures-Linked List

9. Data Structures - Stack

10. Data Structures - Queue

11. Summary Introduced the module Introduced different types of AI Structures

12. Task 1: Finite-state machines

13. Outcomes By the end of the session you should: Understand what a state diagram is. Understand the principles of a finite state machine Describe a simple system using a state diagram Applications using state diagrams

14. What is a state?

15. State diagram (Taken from Picton 2004) Button? Cup? End? yes no yes State 0 wait for the button to be pressed State 1 wait for a cup to be placed State 2 wait for the coffee to be poured

16. Next-state table (Taken from Picton 2004) 00 00 1 111 222 2

17. Where are they used? Designing systems Games

18. Your designing a character for a maze- based game. You must design a state diagram and table for the character.

19. Further reading and references http://en.wikipedia.org/wiki/Finite_state _machine http://en.wikipedia.org/wiki/Finite_state _machine Picton PD (2004) CSY3011 Artificial Neural Networks, University College Northampton