Artificial Intelligence and interdisciplinarity
Bert Kappen
Symposium Neuroscience
Oktober 2012
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Wat is intelligentie?
• Wat is intelligentie?– Evolutionair: hoe is het ontstaan?– Principieel: hoe kan het bestaan?– Praktisch: hoe maak je het?
"Een rol van intelligentie is om onze waarnemingen aan te vullen waar deze tekort schieten, en is het
gevolg van de beperkingen van onze zintuigen en van de onzekerheid in de wereld om ons heen."
1. Evolutionair perspectief
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Intelligentie is een vorm van patroonherkenning
Is intelligent gedrag verenigbaar met de wetten van de natuur?
2. Principieel perspectief
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Plenz Chialvo 2010
Complexe dynamische systemen zijn deterministischen onvoorspelbaar
Menselijk gedrag is mechanisch en onvoorspelbaar
Intelligent gedrag vereist complexe berekeningen en efficiente algoritmes
Patroonherkenning, redeneren, leren, control,…..
3. Praktisch perspectief
The digital age
Unification of AI
Chess playing as search (Shannon, 1950)
Logic Theorist (Newell and Simon, 1956)
Learning checkers player (Samuel, 1952)
Intelligent machines
General purpose search (brute force) not only faces complexity, but also gives non-sense results:
"the spirit is willing but the flesh is weak"
"the wodka is good but the meat is rotten"
Expert systems
p(ab)=p(a|b)p(b) p(a)+p(not a)=1
Modern AI uses probability theory
Bayes rule: p(b|a)p(a)=p(a|b)p(b)
disease=yes,no test=yes,no
d
t
Bayes’rule
p(d=1)=0.01 p(d=0)=0.99p(t=1|d=1)=0.95 p(t=0|d=1)=0.05P(t=1|d=0)=0.05 p(t=0|d=0)=0.05
A disease has prevalence of 1 %. A test has an accuracy of 95 %John does the test and the result is positive.What is the probability that John has the disease?
P(d=1|t=1) = p(t=1|d=1) p(d=1)/p(t=1)p(t=1|d=1) p(d=1)=0.95*0.01=0.0095p(t=1)=p(t=1|d=0)p(d=0)+p(t=1|d=1)p(d=1)=0.05*0.99+0.95*0.01=0.059p(d=1|t=1)=0.0095/0.059=0.16
Bayes Rule
•Learning:
–X parameters
–Y training data
p(x|y)=p(y|x)p(x)/p(y)
Bayes Rule
•Inference:
–X diagnoses
–Y patient findings
p(x|y)=p(y|x)p(x)/p(y)
Bayes Rule
•Localization:
–X locations
–Y images
database
PCA
Off-line
x
y
p(x|y)=p(y|x)p(x)/p(y)
Graphical models
What are probabilities given evidence:
Intractable for large number of variables: 2n for binary variables
Unification of AI
Most interesting problems are hard
10 1 sec
20 20.000 sec
30 15 year
40 300.000 year
50 1010 year
Complexity
Methods from physics help out
Methods from physics help out
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Control as inference
• Probe the system with uncontrolled trajectories
• Choose the ones that are most successful
• Steer according to their initial direction
• Improve probing and iterate
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Result after 100 trials of motor babblingNo model assumed
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Application in robotics
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Summary
• Research on intelligence is interdisciplinary:– Computer science, physics, neuroscience,
engineering, robotics, statistics, mathematics
• Real progress is hard:– Hard mono-disciplinary problems
• Complexity of computation, “what does the brain compute?”
– Interdisciplinary paradigm clashes and resolutions
• Bayesian revolution, Control as Statistical physics38
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Interdisciplinary research
• Interdisciplinary research profits from low hanging fruit
• Society wants quick results
Mono-disciplinary‘Deep and slow’
Established research paradigm
Inter-disciplinary‘Shallow and fast’
no established research paradigm
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Interdisciplinary research
• The role of industry– Industry has limited vision of fundamental
research (top sectoren beleid)– Participation of companies in publicly funded
research sometimes confuses ‘relevance for society’ with ‘relevance for the company’.
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