Artificial Intelligence Techniques Introduction to Artificial Intelligence.

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Presentation transcript:

Artificial Intelligence Techniques Introduction to Artificial Intelligence

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.

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

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

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

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

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

Data Structures-Linked List

Data Structures - Stack

Data Structures - Queue

Summary Introduced the module Introduced different types of AI Structures

Task 1: Finite-state machines

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

What is a state?

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

Next-state table (Taken from Picton 2004)

Where are they used? Designing systems Games

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

Further reading and references _machine _machine Picton PD (2004) CSY3011 Artificial Neural Networks, University College Northampton