Transcript TDT 4136 Logikk og Resonnerende Systemer

TDT 4136 Logikk og
Resonnerende Systemer
http://www.idi.ntnu.no/emner/tdt4136/
http://www.idi.ntnu.no/~toreamb/
JAVA/Newlogo.html
Overall course structure
AI Artificial
Intelligence
(A modern approach)
AI-1
Fall semester
AI-2 Spring semester
TDT 4136
TDT4171
Logic and
reasoning systems
Methods in
artificial
intelligence
Course prehistory
Before
IT2702
Artificial Intelligence
TDT 4125
TDT4170
Logic
Knowledge systems
Now
TDT4136
TDT4171
Logic and reasoning
systems
Methods in artificial
intelligence
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 Intelligence
Artificial 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
ARTIFICIAL
INTELLIGENCE
Artificial horse ?
HORSE
INTELLIGENCE
The Intelligence Pyramid
Each level is a set of
relations on the level
below
Wisdom
Intelligence
Knowledge
Information
Data
Noise
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
Expertise (50 cents
Expertise (50 cents)
If most people prefer the
computer to the human
expert, the computer has
artificial expertise.
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
interface:
Question-andanswer
Knowledge base
Knowledgebase editor
Menu driven
User
Natural
language
Graphic
inteface
Expert system shell
Inference
engine
General
knowledgebase
Case-specific
data
Explanation
subsystem
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?
Are we machines ?
Can silicon computers think ?
If humans are machines, then machines can think.
Even if machines made of proteins can think, perhaps ones
made of silicon does not.
(Searle, 1992) Chinese room scenario
What is understanding ?
Searle’s Chinese Room
Does the system understand Chinese ?
Is the system conscious ?
What if John has the rules in his head ?
 John
Rules
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.