Introduction to Artificial Intelligence ARTIFICIAL INTELLIGENCE TECHNIQUES Artificial

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Introduction to Artificial Intelligence ARTIFICIAL INTELLIGENCE TECHNIQUES

Introduction to Artificial Intelligence ARTIFICIAL INTELLIGENCE TECHNIQUES

Artificial Intelligence AI is often divided into two basic ‘camps’ Rule-based systems (RBS) Biological

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

In the module Evolutionary algorithm Neural networks Fuzzy Logic Expert Systems and Knowledge Processing

In the module Evolutionary algorithm Neural networks Fuzzy Logic Expert Systems and Knowledge Processing Searching Internet and AI

Examples Focus of the applications is the early part of the module is on:

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

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

Example Areas

Example Areas

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

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

The Ingredients( Taken from: Evo. Net Flying Circus www 2. cs. uh. edu/~ceick/ai/EC 1.

The Ingredients( Taken from: Evo. Net Flying Circus www 2. cs. uh. edu/~ceick/ai/EC 1. ppt ) t reproduction selection mutation recombination t+1

Depth-First Search Taken from Jones (2005)

Depth-First Search Taken from Jones (2005)

Breadth-First Search Taken from Jones (2005)

Breadth-First Search Taken from Jones (2005)

Knowledge Processing Introduce types of reasoning Deterministic Propositional logic Predicate logic Dynamic-non-monotonic Non-deterministic

Knowledge Processing Introduce types of reasoning Deterministic Propositional logic Predicate logic Dynamic-non-monotonic Non-deterministic

Using an Expert System Taken from Johnson and Picton (1995)

Using an Expert System Taken from Johnson and Picton (1995)

Internet and ‘AI’ Week A – AI on internet, basic introduction to semantic web,

Internet and ‘AI’ Week A – AI on internet, basic introduction to semantic web, agents. Week B – Microformats Week C – Collective Intelligence and searching 1 Week D – Collective Intelligence and searching 2

Basic structures

Basic structures

Data Structures-Linked List

Data Structures-Linked List

Data Structures - Stack

Data Structures - Stack

Data Structures - Queue

Data Structures - Queue

Summary Introduced the module Introduced different types of AI Structures

Summary Introduced the module Introduced different types of AI Structures

TASK 1: FINITE-STATE MACHINES

TASK 1: FINITE-STATE MACHINES

Outcomes By the end of the session you should: Understand what a state diagram

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?

What is a state?

State diagram (Taken from Picton 2004) yes State 0 wait for the button to

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

Next-state table (Taken from Picton 2004)

Next-state table (Taken from Picton 2004)

Where are they used? Designing systems Games

Where are they used? Designing systems Games

 Your designing a character for a maze-based game. You must design a state

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

Further reading and references http: //en. wikipedia. org/wiki/Finite_state_mac hine Picton PD (2004) CSY 3011

Further reading and references http: //en. wikipedia. org/wiki/Finite_state_mac hine Picton PD (2004) CSY 3011 Artificial Neural Networks, University College Northampton