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TDT 4136 Logikk og Resonnerende Systemer

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Overall course structure

AI Artificial Intelligence

(A modern approach)

AI-2 Spring semester

TDT4171

Methods in artificial intelligence

AI-1 Fall semester

TDT 4136

Logic and reasoning systems

Course prehistory

TDT 4125

Logic

IT2702

Artificial Intelligence

TDT4170

Knowledge systems

TDT4171

Methods in artificial intelligence

TDT4136

Logic and reasoning systems

Before

Now

What is intelligence ?

Intelligence is the ability to solve new problems based on earlier experience.

SICStus Prolog

Prolog Compiler developed by Swedish Institue of Computer Science (SICS) 1990– (?)

Performance on a fast PC (3.4 GHz)

> 70 MegaLIPS (70 Mill. Logic inferences/second)

What is Artificial IntelligenceArtificial Intelligence is the science of making machines do things that would require intelligence if done by man.

(Prof. Marvin Minsky)

AI is the study of how to make computers do things which at the moment people do better.

(Prof. Elaine Rich)

(Horizon effect: If it works, it is no longer AI)

A Definition of Intelligence

An entity is intelligent if it has an adequate model of the world, it is clever enough to answer a wide variety of questions on the basis of this model, if it can get additional information from the external world when required, and can perform such tasks in the external world as its goals demands and physical abilities permit.

What is AI (N.J.Nilsson)

AI is concerned with intelligent behaviour.

Intelligent behaviour involves perception, reasoning, learning, communicating and acting in complex environments.

AI has as one of its long term goals the development of machines that can do these things as well as humans can.

Another goal is to understand this kind of behaviour. Thus, AI has both engineering and scientific goals.

Artificial Intelligence (AI)

Grand goal is to achieve human level intelligence.

AI was coined at the Dartmouth conference in 1956.

Founding father John McCarthy.

What is ”Artificial”

TRACTOR

INTELLIGENCEHORSE

ARTIFICIAL INTELLIGENCE

Artificial horse ?

The Intelligence Pyramid

Wisdom

Intelligence

Data

Knowledge

Noise

Information

Each level is a set of relations on the level below

Levels of intelligence

7. Can A be alive (not allowed to be killed) ?

6. Can A have a (genuine) consciousness ?

5. Can A feel real feelings (pain,sorrow,happiness)?

4. Can A think ?

3. Can A reason ?

2. Can A deduce ?

1. Can A compute ?

Replace A with human/child/embryo/ape/robot/computer

What is your opinion ?

Aspects of Intelligence

Human likeness (how much does it resemble a human ?)

Human performance (is it as clever as a human ?)

Human like tasking (are humans doing it ?)

Human like operation (are humans doing it similarily?)

Human like genesis (was it made or did it evolve?)

What is AI (James Allen,99)

• AI is the science of making machines that do tasks that humans can do or try to do

•AI is not the science of building artificial people

•AI is not the science of understanding human intelligence (Cognitive Science)

•AI is not even the science of trying to build artifacts that can imitate human behaviours well enough to fool someone that the machine is human (Turings test)

Game Playing

Om May 11 1997, an IBM program DEEP BLUE beat the reigning world champion Garry Kasparov 3.5 – 2.5 in a six game match.

”We won”

The Noble Art of Car Parking

Artificial Expertise

If most people prefer the computer to the human expert, the computer has artificial expertise.

Expertise (50 centsExpertise (50 cents)

Rule Based Systems

Rule based systems / Knowledge based systems/ Expert Systems

have played and plays an important role in the AI industry.

A report from from 1993 by John Durkin:

Reports on Over 2500 Developed Expert Systems

Application areas:

Agriculture, Business, Chemistry, Communications, Computer Systems, Education, Electronics, Engineering, Environment, Geology, Image processing, Information Management, Law, Manufacturing, Mathematics, Medicine, Meteorology, Military, Mining, Power Systems, Science, Space Technology, Transportation

Types of systems:

Rule Based, Frame Based, Fuzzy Logic, Case Based, Neural Network

Architecture of a typical expert system

User

User interface:

Question-and-answer

Menu driven

Natural language

Graphic

inteface

Explanation subsystem

Inference engine

Knowledge- base editor

General knowledge- base

Case-specific

data

Knowledge base

Expert system shell

AI in Medicine (USA 1970)• Stanford

MYCIN - blood infections

• Rutgers

CASNET - casual reasoning

• MIT

PIP - renal disease

• Stanford

• Pittsburgh

Internist – internal medicine

- ”the primary goal of this field is to develop computer programs that perform efficiently and are able to explain their reasoning and conclusions to their users”

Mycin system for diagnosis og meningitis and

bacteremia (bacterial infections) IF

the site of the culture is blood, and

the identity of the organism is

not known with certainty, and

the stain of the organism is gramneg, and

the morphology of the organism is rod, and

the patient has been seriously burned

THEN

there is weakly suggestive evidence (0.4) that

the identity of the organism is pseudomonas

Intelligent Programming/ Programmed Intelligence

For a given task, it is possible to make a program that performs intelligently (Intelligent programming) . Then the intelligence is implicit in the program.

A goal is to make a program for any given set of tasks can perform intelligently without being reprogrammed. (Programmed Intelligence). This requires that the intelligence is represented explicitly.

•Machine Learning

•Genetic Algorithms

•Evolutinary Programming

The Bus Route Oracle BussTUC

BussTUC is a natural language expert system for bus departures in Trondheim.

It is written in Prolog ( > 110.000 program lines) and answers > 800.000 queries/year (2007)

Game of Life,

Example of Artificial life

Artificial Intelligence versus Cognitive Science

Although a computer can do logical reasoning, it does not mean that the computer is trying to simulate a human.

In fact, computers can do logical reasoning better than humans.

We can say, with a twist, that AI is the science of correct thinking, while CS is the science of incorrect thinking. (Errare humane est).

Tower of Hanoi Puzzle

Cognitive Science: How do humans solve the TOH problem?

Artificiel Intelligence: How can we make the machine solve it efficiently and autonomously?

Even if machines made of proteins can think, perhaps ones made of silicon does not.

(Searle, 1992) Chinese room scenario

Are we machines ?

Can silicon computers think ?

If humans are machines, then machines can think.

What is understanding ?Searle’s Chinese Room

Rules

John

Does the system understand Chinese ?

Is the system conscious ?

What if John has the rules in his head ?

Physical Symbol System Hypothesis

That hypothesis states that a physical symbol system has the necessary and sufficient means for general intelligent action.

(Newell&Simon, 1976)

A physical symbol system is a machine, like a digital computer that is capable of manipulating symbolic data.

It doesn’t matter what the physical symbol system is made of.