Artificial Intelligence, simulation and modelling.

Slides:



Advertisements
Similar presentations
Information and Software Technology Option: Artificial intelligence, simulation and modelling.
Advertisements

Information and Software Technology
Artificial Intelligence and Expert Systems
Artificial Intelligence
ICT IGCSE Expert Systems.
An Introduction to Artificial Intelligence. Introduction Getting machines to “think”. Imitation game and the Turing test. Chinese room test. Key processes.
4 Intelligent Systems.
Will Androids Dream of Electric Sheep? A Glimpse of Current and Future Developments in Artificial Intelligence Henry Kautz Computer Science & Engineering.
C SC 421: Artificial Intelligence …or Computational Intelligence Alex Thomo
Chapter 11 Artificial Intelligence and Expert Systems.
SESSION 10 MANAGING KNOWLEDGE FOR THE DIGITAL FIRM.
1 Chapter 2 Uses and Limitations. 2 Chapter 2 Contents l The Chinese Room l HAL – Fantasy or Reality? l AI in the 21 st Century.
Chapter 12: Intelligent Systems in Business
“Get outa here!”.
Building Knowledge-Driven DSS and Mining Data
McGraw-Hill/Irwin ©2005 The McGraw-Hill Companies, All rights reserved ©2005 The McGraw-Hill Companies, All rights reserved McGraw-Hill/Irwin.
An expert system is a package that holds a body of knowledge and a set of rules on a subject that has been gained from human experts. An expert system.
ICT in Healthcare Expert Systems.
Artificial Intelligence
3.11 Robotics, artificial intelligence and expert systems Strand 3 Karley Holland.
Artificial Intelligence
Expert Systems Infsy 540 Dr. Ocker. Expert Systems n computer systems which try to mimic human expertise n produce a decision that does not require judgment.
Artificial Intelligence By Ryan Shoultes & Jeremy Creighton.
Expert System Note: Some slides and/or pictures are adapted from Lecture slides / Books of Dr Zafar Alvi. Text Book - Aritificial Intelligence Illuminated.
Succeeding with Technology Information, Decision Support… Decision Making and Problem Solving Management Information Systems Decision Support Systems Group.
Artificial Intelligence Lecture No. 15 Dr. Asad Ali Safi ​ Assistant Professor, Department of Computer Science, COMSATS Institute of Information Technology.
Chapter 14: Artificial Intelligence Invitation to Computer Science, C++ Version, Third Edition.
Chapter 10 Artificial Intelligence. © 2005 Pearson Addison-Wesley. All rights reserved 10-2 Chapter 10: Artificial Intelligence 10.1 Intelligence and.
11 C H A P T E R Artificial Intelligence and Expert Systems.
Artificial Intelligence Introductory Lecture Jennifer J. Burg Department of Mathematics and Computer Science.
Artificial Intelligence
Copyright © 2006, The McGraw-Hill Companies, Inc. All rights reserved. Decision Support Systems Chapter 10.
Computing Fundamentals Module Lesson 19 — Using Technology to Solve Problems Computer Literacy BASICS.
Information Systems & Databases 2.1) Information Systems.
Fundamentals of Information Systems, Third Edition2 Principles and Learning Objectives Artificial intelligence systems form a broad and diverse set of.
Information knowledge based systems (IKBS) and expert systems.
Chapter 13 Artificial Intelligence and Expert Systems.
Artificial Intelligence and Expert Systems. ARTIFICIAL INTELLIGENCE (AI) is the science of R L Being able to Ability to solve a problem.
Fundamentals of Information Systems, Sixth Edition1 Natural Language Processing and Voice Recognition Processing that allows the computer to understand.
I Robot.
Impact of ICT on Society – Part the first ICT 1_6.
Soft Computing Lecture 19 Part 2 Hybrid Intelligent Systems.
Expert Systems. L EARNING O BJECTIVES : By the end of this topic you should be able to: explain what is meant by an expert system describe the components.
Artificial intelligence
Computing Fundamentals Module Lesson 6 — Using Technology to Solve Problems Computer Literacy BASICS.
Fundamentals of Information Systems, Third Edition1 The Knowledge Base Stores all relevant information, data, rules, cases, and relationships used by the.
Artificial Intelligence, Expert Systems, and Neural Networks Group 10 Cameron Kinard Leaundre Zeno Heath Carley Megan Wiedmaier.
ARTIFICIALINTELLIGENCE ARTIFICIAL INTELLIGENCE EXPERT SYSTEMS.
Introduction to Artificial Intelligence CS 438 Spring 2008.
Fundamentals of Information Systems, Third Edition 1 Information and Decision Support Systems: Management Information Systems Management information system.
Expert Systems. Learning Objectives: By the end of this topic you should be able to: explain what is meant by an expert system describe the components.
O NCE TRADING BEGINS, PLEASE ALLOW IT TO TRADE O NCE TRADING BEGINS, PLEASE ALLOW IT TO TRADE B E REALISTIC WITH YOUR EXPECTATIONS B E REALISTIC WITH.
ITEC 1010 Information and Organizations Chapter V Expert Systems.
 Ease the managing task  Guide for problem solving & decision making  Advance in carrier. Realise opportunities and meet personal and company goals.
ARTIFICIAL INTELLIGENCE. Contents Introduction Branches of AI Control Theory Cybernetics Artificial Neural Networks Application Advantage And Disadvantage.
Using Technology to Solve Problems Unit 2 Mod 2 SO 7.
COMPUTER SYSTEM FUNDAMENTAL Genetic Computer School INTRODUCTION TO ARTIFICIAL INTELLIGENCE LESSON 11.
Bennie D Waller, Longwood University Bennie D. Waller Longwood University 201 High Street Farmville, VA Intelligent Information Systems.
CHAPTER ELEVEN MANAGING KNOWLEGE. Objectives We have been through some of this already Role of knowledge management Types of knowledge management systems.
Decision Support and Business Intelligence Systems (9 th Ed., Prentice Hall) Chapter 12: Artificial Intelligence and Expert Systems.
Fundamentals of Information Systems
CHAPTER 1 Introduction BIC 3337 EXPERT SYSTEM.
Organization and Knowledge Management
Introduction Characteristics Advantages Limitations
Artificial Intelligence and Society
MANAGING KNOWLEDGE FOR THE DIGITAL FIRM
Artificial Intelligence and Expert Systems
Future of Artificial Intelligence
Artificial Intelligence
Artificial Intelligence Machine Learning
Presentation transcript:

Artificial Intelligence, simulation and modelling

Artificial Intelligence Your computer can do lots of things automatically: -spelling mistakes in a word-processed document can be identified and automatically corrected; -games can be played against a computer, where the computer often wins; computers can fly planes -robots can carry out a variety of tasks. These are all examples of applications that come from developments in the study of artificial intelligence.

Understanding AI Intelligence is more than the amount of knowledge a person has. It includes the ability to think, solve problems and make conclusions based on available information. Reasoning - to solve a problem logically and draw conclusions Empathy - to understand what it's like to be another person, or to be in a another situation Predicting - to foretell a future situation Decision-making - based on a range of factors Communicating - using written and oral languages Experiencing emotions - and being socially competent.

Artificial intelligence involves the development of computer systems that model human thinking processes to imitate some human ability or behaviour

Uses of AI Medical Robot control Household and pets Finance – banks, trading Online – avatars Toys and games Music Aviation

Some of these are ok too… robots.htm

Today! Select a AI development. Create a poster to inform others of this AI Research the impact this development has had in different work fields and todays society. Include a picture!

Areas of Artificial Intelligence Intelligent Systems An intelligent system is a system with artificial intelligence that is able to use the available data to make decisions. Computers that play strategy games (such as chess) are examples of intelligent systems.

Knowledge Bases An intelligent system needs to be given a set of rule or facts in order to make decisions. These rules or facts are often called a knowledge base. They also include the knowledge or subject content, which is organised in a logical order for decision making. Knowledge bases contain two types of knowledge: Factual - information found in texts or widely known facts Heuristic - general rules or probabilities rather than specific instructions. In many instances, these are stored as IF±THEN statements such as: IF a specific condition exists, THEN specify actions or conclusions E.g. Medical Knowledge -Facts – detail about the diseases and symptoms -Heuristics – how to diagnose particular diseases.

Tasks 1/ _nolan.shtml

Demons Demons are programs that are activated when a value is triggered. For example, the anti-virus software on your computer uses a demon. It activates when an arrives, identifying specific file types that indicate that a virus is present. Most demons operate automatically without the user's knowledge.

Agents An agent is a program that performs a processing or information-gathering task. Search engines on the World Wide Web use agents, and some of these agents can be given specific instructions to collect a certain type of information. An agent is used when you shop online and pay by credit card. An agent will automatically locate and retrieve requested data

Expert Systems An expert system is a program that provides recommendations or decisions about a problem. They are the most common form of intelligent system. To use an expert system, data about a problem is entered into the expert system. An inference engine then examines each part of the problem, using the facts and rules in its knowledge base, to make decisions or recommendations. Examples – medical diagnosis, legal, accounting, customer and IT support, character simulation in games

Expert Systems Example IT help desk Helps diagnose computer problems – monitor not working Data about the computer problem is entered into the expert system which then looks in the knowledge base to determine possible solutions to the problem. We look at this in more detail later.

Neural Networks The human brain is a neural network, with neurons acting as the connecting devices in the nervous system. An artificial neural network is a computer system which has a design based on the way the human brain works. It operates by creating connections between processors, the computing equivalent of neurons. Artificial neural networks are capable of learning – similar to the way expert systems work by following a set of rules Good at recognising complex patterns. They are used in voice recognition programs (trained). As well as image recognition etc.

Task 1.Outline the link between an expert system and a knowledge base. 2.What are the advantages and disadvantages of expert systems? 3.Find examples and present them in a table of the uses of demons, agents, expert systems, neural networks and knowledge bases in businesses in our local community 4.What is the Chinese room argument? – What is your view on this argument?