Metaphors to AI - w3.ualg.ptw3.ualg.pt/~jvo/ia2015-16/ia2015-16T3.pdf · 1985: ALVINN, “an...

1

Stuart Russel and Peter Norvig, Artificial Intelligence: A modern approach, 3rd edition, Pearson Education, 2010 http://aima.cs.berkeley.edu/

Ernesto Costa e Anabela Simões, Inteligência Artificial: Fundamentos e Aplicações (2ª edição) FCA, Set. 2008

Metaphors to AI

5-Feb-16 http://w3.ualg.pt/~jvo/ia 2-2

2


Metaphors

Computational

Conexionists

Biological


Previously on AI: 8-puzzle, the classical example

1 2 34

5678

1 2 34

567

8

1 2 34 56

78

1 23456

78

1 2 34 56

78

1 2 34 56 7 8

(Objectivo)

(Nó inicial)

3


Approaches or metaphors

Computational

Conexionists

Biological

Brain Initiative: US$ 100 biliões for maping the brain (April 2013)

http://g1.globo.com/ciencia-e-saude/noticia/2013/04/obama-lanca-projeto-de-us-100-milhoes-para-mapeamento-do-cerebro.html

4

The Human Brain Project (EU, October 2013)

https://www.humanbrainproject.eu/

5-Feb-16

Basic assumptions of neurocomputation

Animals are able to react adaptively to changesin their environment, using their nervoussystems

A suitable model/simulation of the nervoussystem should be able to produce similarresponses and behaviours in artificial systems

The nervous system is built by relatively simpleunits, the neurons

5

5-Feb-16

A microscopic photo of a neuron

5-Feb-16

Other (mainstream) assumptions

Cognition emerges from complex synapticinteractions among many simple neurons

Relevant neuronal information is completelymembrane-based (i.e., Hodgkin-Huxley neuron)

Synaptic strengths mediate memory andlearning (e.g., Hebb, Long Term Potentiation)

Classical bayesian probabilities govern cognition

6

5-Feb-16

Communication

5-Feb-16 http://w3.ualg.pt/~jvo/rnsd

Biologic and artificial neurons

axon

cell body

synapse

nucleus

dendrites

x1x2xixn

w1w2wiwn

+ oSigmoide

16 – 12

7

5-Feb-16 http://w3.ualg.pt/~jvo/rnsd

The Rosenblatt’s perceptron, 1957

16 – 13


Abordagem conexionistaO cérebro como modelo

As redes neuronais artificiais são dos sistemas (estatísticos) de aprendizagem mais populares e efectivos

Gozam de características como:Processamento massivamente paralelo e distribuídoTolerante a ruído e a informação completaDegradação suave a falhasSão aproximadores universaisSão capazes de generalizar

8


Approaches or metaphors

Computational

Conexionists

Biological

From:http://www.nature.com/nature/journal/v45

6/n7219/full/456175a.html 2-16

Why do intelligent people live longer?

“Intelligence can predict mortality more strongly than body mass index, totalcholesterol, blood pressure or blood glucose, and at a similar level tosmoking”, (…) “But the reasons for this are still mysterious. That needs tochange. Reducing health inequalities is a priority, and to do that we need todetermine their causes.” (Ian Deary, 2008)

9

5-Feb-16 11 – 17

PopulationIndividualCellChromossomeDNAGeneAleloLocus

Basic Biology

5-Feb-16 11 – 18

From Biology to Algorithms: TerminologyGene – An single encoding of part of a solution.

Chromosome – A string of “genes” that represents a solution.

Population - The number of “chromosomes” available to test.

10

5-Feb-16 11 – 19

Random initial population

f(x)

x

GA as parallel stochastic search

1010001110 0011010010

5-Feb-16 11 – 20


Parents: 1010001110 0011010010

Offspring: 1010010010 0011001110

Randomly chosen position

11

5-Feb-16 11 – 21

f(x)

x


Random initial population

After some iterations

After selection and reproduction

General Scheme of EAs

12

A brief history of AI


5th century BCAristotle proposes syllogistic logic, the first deductive reasoning system.

pré AI

13


17th centuryDescartes proposes that animals are machinesand founds a scientific paradigm that willdominate for 250 years: Cogito ergo sum

Pascal creates the first mechanical calculator in1642

pré AI


19th centuryGeorge Boole creates a binary algebra to represent “laws of thought”

Charles Babbage and Lady Lovelace develop sophisticated programmable mechanical computers, precursor to modern electronic computers.

pré AI

14


1943: Warren McCulloch and Walter Pitts laythe groundwork for neural networks

1949: Donald Hebb writes the book TheOrganization of Behavior

After WWII


1950 – Alan Turing proposes a test formachine intelligence

1956 – John McCarthy coins the term“artificial intelligence”

1959 – Arthur Samuel’s checkersprogram wins games against the besthuman players

1962 – First industrial robot company,Unimation, founded

1967 – “HAL” stars in “2001: A SpaceOdyssey”

1969 – Stanford Research Institute:Shakey the Robot demonstratedcombining movement, perception andproblem solving

15


1971 – Terry Winograd’s PhD thesis (M.I.T.) demonstrated the ability of computers to understand English sentences in a restricted world of children’s blocks

1975 - John Holland’s book Adaptation in Natural and Artificial Systems formalizes and popularizes evolutionary algorithms

Terry Winograd

John Holland


1971: Terry Winograd demonstrates a program that can understand English commands in the word of blocks.

1972: Alain Colmerauer writes Prolog

1974: Ted Shortliffe creates MyCin, an expert system using uncertainty management, and that showed the effectiveness of rule-based knowledge representation for medical diagnosis.

Knowledge-based season

16


1975: John Holland proposes Genetic Algorithms

1978: Herb Simon wins Nobel Prize for his theory of bounded rationality

1980’s: Backpropagation (invented 1974) rediscovered and sees wide use in neural networks

The birth of nouvelle AI


1985: ALVINN, “an autonomous land vehicle in a neural network” navigates across USA.

1986: Rumelhart and McClelland, Parallel distributed Processing

1987: Christopher Langton coined the term “Artificial Life”

Connectionism revival

17


1990-91 – AI technology plays a key role in the Gulf War, from automated co-pilots and cruise missiles, to overall battle coordination, and more

1997 – IBM supercomputer Deep Blue defeats world chess champion Garry Kasparov in a 6-game match

1998 -present -- Google leverages an increasing arsenal of narrow-AI technologies to provide commercially successful Web search and ad delivery

2001 - Lionhead Studio releases Black and White, a popular videogame in which players teach AI-controlled creatures using imitative and reinforcement learning

Google’s FirstServer

Creature from Black & White

Gulf War

Deep Blue


1995: The emergence of intelligent agents

1997: Deep Blue II defeats Garry KasparovRosalind Picard, Affective Computing, MIT Press

2011:Watson competed on Jeopardy! and won a first prize of $1 million

… up to yesterday

18


Jan 2016: GO – humans not ahead anymore

… up to today


Where are we?Introduction

The State of the ArtDefinitionsStrong vs. weak AI Success criteria: the Turing testLimits to computabilityFoundations of AI Metaphors of AIA brief history of AI

Metaphors to AI - w3.ualg.ptw3.ualg.pt/~jvo/ia2015-16/ia2015-16T3.pdf · 1985: ALVINN, “an...

Documents

Transcript of Metaphors to AI - w3.ualg.ptw3.ualg.pt/~jvo/ia2015-16/ia2015-16T3.pdf · 1985: ALVINN, “an...