A Brief History 1 Great Expectations It is not my aim to surprise or shock you but the simplest way I can summarize is to say that there are now in the world machines that think that learn and that create Moreover their ability to do these things is going to increase rapidly until in ID: 434880
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Artificial IntelligenceA Brief History
1Slide2
Great Expectations
It is not my aim to surprise or shock you – but the simplest way I can summarize is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until – in a visible future – the range of problems they can handle will be coextensive with the range to which the human mind can be applied.
We have invented a computer program capable of thinking non-numerically, and thereby solved the venerable mind-body problem.
Herbert Simon, 1957r.
2Slide3
Early Successes
Logic Theorist
proved
38
out of 52 theorems of Chapter 2 of Principia MathematicaGeometry Theorem Prover proved theorems too hard for undegraduate students in mathematics
ELIZA
, computer-based psychoterapist helped many hypochondriacs
MYCIN, an expert system to diagnose blood infections, was able to perform considerably better than junior doctors
3Slide4
Trouble
Solutions developed for „microworlds” did not apply in the real world (computational complexity)Expert systems could not be extended to broader domains (context)
Fiasco of the automatic translation project (context)
The spirit is willing but the flesh is weak
The vodka is good but the meat is rottenFiasco of the planning systems (the frame problem)
4Slide5
Planning
A
C
B
D
S1
T[On(B,A), S1]
T[Clear(B), S1]
T[Clear(C), S1]
T[Clear(D), S1]
A≠B ≠C ≠D
Plan a sequence of actions
α
=<A1,...,An> such that:
T[On(A,C), Result(
α
,S1]
T[On(D,A), Result(
α
,S1]
5Slide6
Planning, cont.
Available actions:
stack: S(x,y)
unstack: U(x,y)For every atomic action we specify their effects through axioms:
T[Clear(x), S] &
T[Clear(y), S] & x ≠ y →
T[On(x,y), Result(<S(x,y)>, S)]
T[On(x,y), S] & T[Clear(x), S] →
T[Clear(y), Result(<U(x,y)>, S)]
6Slide7
Planning, cont.
A
C
B
D
D
C
A
B
D
C
A
B
D
C
A
B
U(B,A)
S(A,C)
S(D,A)
7Slide8
Planning - proof
T[On(B,A), S1]
T[Clear(B), S1]
T[Clear(A), S2], where S2=Result(<U(B,A)>,S1)
T[Clear(C),S2) T[On(A,C), S3], where S3=Result(<S(A,C)>,S2)
Ad hoc solution – let’s add frame axioms for the
unstack
action:
T[Clear(x), S] → T[Clear(x), Result(<U(y,z)>,S)]
false!
8Slide9
The Frame Problem (AI version)
How to formalize changes (and lack thereof) in the world as a result of our actions.
Adding the frame axioms does not solve the problem:
It is impractical (we would need millions of such axioms)
It is not intuitive (we do not do it!)It is often false (what should we do when one robot is moving the blocks while another one is painting them?)
9Slide10
Default Logic
Commonsense law of inertia: things stay as they are unless we have knowledge to the contrary.
Default rule where
α
,
β
,
γ
are formulas.
Once
α
has been established and
β
is consistent with what we know, we conclude
γ
.
Example: take the generic truth„Birds fly”. In Default Logic we write this as:
If we know that Tweety does not fly (because he is an ostrich), the rule will not fire
despite the fact
that Tweety is a bird.
10Slide11
Default Logic: theory
E is an extension of <W,D> iff there exist E
0
, E
1, E2
, ... such that:
11Slide12
Default Logic: example
Quaker
Pacifist
Nixon
Republican
W={R(nixon), Q(nixon)}
This theory has two extensions:
12Slide13
Default Logic: problem
This theory also has two extensions. This time, however, this does not agree with our intuitions.
Amish
Speaks German
Born in
Pennsylvania
Born in the USA
Hermann
We solved the Frame Problem to face the problem of relevance.
13Slide14
The Frame Problem in Philosophy: Dennett
Odpowiednikiem problemu ramy w AI jest zagadka myślenia potocznego
Wydaje się, że większość naszych działań
nie
jest planowana Na pewno nasza cała wiedza nie jest reprezentowana w postaci zdań (pojemność i szybkość mózgu)Niemal zawsze rozumujemy używając zastrzeżenia ceteris paribusPotrafimy bez trudu rozróżnić co jest, a co nie jest istotne
dla realizacji naszych działań w danej sytuacji
14Slide15
The Epistemological Frame Problem
Jak opisać istotność w postaci zdań logiki, gdy istotność jest holistyczna, otwarta i wrażliwa na kontekst?
The Computational Frame Problem
Jak ograniczyć proces rozumowania do tego co istotne, gdy istotność jest holistyczna, otwarta i wrażliwa na kontekst?
15Slide16
The Frame Problem in Philosophy: Fodor
The Metaphysical Frame Problem:
Zdroworozsądkowe prawo inercji uzasadnione jest tylko w kontekście właściwej ontologii. Jaka to ontologia?
Ontologia z pojęciami takimi jak
ziebieski i fridgeon falsyfikuje zdroworozsądkowe prawo inercji. W tym sensie Problem Ramy to jescze jedno oblicze problemu indukcji.
16Slide17
What Next?
17Slide18
Path 1: Stay the CourseProjekt CYC
The problem of AI is commonsense knowledge: let’s add it then!
Goals:
30 people are entering data from newspapers, ads, disctionaries, etc.
After 6 years a million assertions have been entered; the goal was 100 millionCYC had its own ontology, representations of causal relationships and simple rules of relevance
The project came to an end in 1994 r. (after 50 mln $); its remnants are still around today
EN
CYC
LOPEDIA
18Slide19
Path 2: Change the Paradigm
Dreyfus’s criticism: AI’s basic assumptions are wrong!
Biological assumption: the brain is a symbol-manipulating device like a digital computer.
Psychological assumption: the mind is a symbol-manipulating device like a digital computer.
Epistemological assumption: intelligent behavior can be formalized and thus reproduced by a machine.Ontological assumption: the world consist of independent, discrete facts.19Slide20
Path 2: cont.
Filozoficzni przodkowie AI (według Dreyfusa):Kartezjusz: wszelkie rozumowanie polega na manipulacji reprezentacjami symbolicznymi złożonymi z prostych idei
Kant: wszelkie pojęcia można zbudować z prostych elementów przy użyciu reguł
Frege: reguły można sfromalizować tak, by używać ich bez konieczności ich rozumienia lub interpretacji
20Slide21
Path 2 cont.
Mind (intelligence) is:situated in the environment (Heidegger:
In-der-Welt-sein
)
embodied (Merleau-Ponty: le corps propre)AI Lab at MIT (Rodney Brooks) builds the first robots following these tenets (e.g. Big Dog).Dreyfus’s views are further developed by: Andy Clark, John Haugeland, Michael Wheeler, Walter FreemanNew trends in cognitive science:
embodied cognition, dynamicism, neurophenomenology, neurodynamics
...
21Slide22
Path 3: Change the Goal
Distinguish between strong
and
weak
AIStrong AI: we build machines that really thinkWeak AI: we build machines that behave as if they were thinkingWe are only interested in the weak AIEven weaker version: we build machines that behave rationallyWe stay with the logistic approach
22Slide23
Path 3: State of the Art
Which of the following can be done at present?
Play a decent game of table tennis Drive safely along a curving mountain road Drive safely along Telegraph Avenue Buy a week’s worth of groceries on the web Buy a week’s worth of groceries at Berkeley Bowl Play a decent game of bridge
Discover and prove a new mathematical theorem
Design and execute a research program in molecular biology
Write an intentionally funny story Give competent legal advice in a specialized area of law
Translate spoken English into spoken Swedish in real time
Converse successfully with another person for an hour
Perform a complex surgical operation
Unload any dishwasher and put everything away
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Path 3: State of the Art
Which of the following can be done at present?
Play a decent game of table tennis Drive safely along a curving mountain road Drive safely along Telegraph Avenue Buy a week’s worth of groceries on the web Buy a week’s worth of groceries at Berkeley Bowl
Play a decent game of bridge
Discover and prove a new mathematical theorem
Design and execute a research program in molecular biology
Write an intentionally funny story
Give competent legal advice in a specialized area of law
Translate spoken English into spoken Swedish in real time
Converse successfully with another person for an hour
Perform a complex surgical operation
Unload any dishwasher and put everything away
24Slide25
AI and Cognitive Science
AI 50 years ago
Cognitive
Science
AI today
Logic
Thinking
Acting
Rationally
Humanly
The central question in the discussion about the methodology of AI : can AI learn from Cognitive Science?
Has aeronautics learn anything from ornitology?
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