M366: Natural and artificial intelligence 8 credits course, one semester Pre-requisite course: M263 Two TMAs (20%), one MTA(30%) and one final

exam (50%) Like any other AOU course, to pass the course you

have to get: A Minimum of 40% on the CA (TMA and MTA) A Minimum of 40% on the final exam A Minimum of 50% for the average of the CA and the

final

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Course Structure

The course is divided into six blocksA total of 17 units

Block 1: intelligent machines Unit 1 Machines, minds and computers

Block 2: Symbolic intelligence Unit 1 Fundamentals of symbolic AI Unit 2 Search Unit 3 Symbolic AI in the world Unit 4 Has symbolic AI failed

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Course Structure: the units

Block 3: Natural intelligence Unit 1 Natural intelligence Unit 2 Mechanism of natural intelligence Unit 3 Interaction and emergence in swarms Unit 4 Interaction, emergence, adaptation and selection in

individuals

Block 4: Neural networks Unit 1 Mechanism Unit 2 Layers and learning Unit 3 Unsupervised learning in layers and lattices Unit 4 It’s about time: recurrence, dynamics and chaos

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Course Structure: the units

Block 5: Evolutionary computation Unit 1 Unleashing the gene genie, an introduction to

evolutionary algorithms Unit 2 Genetic algorithms Unit 3 Artificial evolution

Block 6: Reflections Unit 1 Intelligence, mind and consciousness

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Block I, Unit 1 Machines, minds and computers

This unit has two main aims:

1. Reviewing the development of human thinking about machines and our mental ability

2. Presenting historical and technical issues that lead to Cybernetics and Symbolic AI

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Block I, Unit 1 Machines, minds and computers

This unit focuses on:

1. Machines

2. Minds

3. Artificial intelligence

4. Computers

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The early beginning: Hephaestus (god of fire) in the old Greek, created Talos, a gigantic mechanical man of bronze, guardian of Crete. (Iliad, XVIII)

Automata (around 1495), Leonardo da Vinci constructed an automaton in the form of armored man capable of moving its arms and simulating speech.

Vaucanson’s duck (1800’s) Game-playing automata: the Turk (1770), Deep blue

of IBM 1997) Robots

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Block I, Unit 1 Machines

Why build such artificial entities? What sort of thing did people think these entities

actually were? What has been the public attitude to the idea of

artificial creatures? Inspired by myths and early creatures, mechanical

pictures start to appear by thinkers of the 17th and the 18th centuries

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Block I, Unit 1 Machines

An intellect which at a certain moment would know all forces that set nature in motion, and all positions of all items of which nature is composed, if this intellect were also vast enough to submit these data to analysis, it would embrace in a single formula the movements of the greatest bodies of the universe and those of the tiniest atom; for such an intellect nothing would be uncertain and the future just like the past would be present before its eyes.

Source: Laplace, Celestial Mechanics (1799–1825)

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Block I, Unit 1 Machines

What is mind ? Mind and body: Debate between monist and dualist

Thomas Hobbes (1588-1679): The world consists only of particles of matter in motion. Bodies and minds are also just particles of matter in motion.

Their motions are caused, in part, by the effects of the movements of particles outside the body, which press on the senses, causing particles in our minds to move in sympathy.

The particles in our minds form parcels: that is, symbols representing concepts such as number, time, names, and so on.

Thought amounts to a form of computation, in which these mental symbols are added, subtracted, etc., in processes similar to those of arithmetic.

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Block I, Unit 1 Minds

Cybernetics: definitions "a science concerned with the study of systems of any nature which are capable of

receiving, storing, and processing information so as to use it for control"-A.N. Kolmogorov

"Cybernetique= the art of growing"--A.M. Ampere "the science of control and communication in the animal and the machine"-Norbert

Wiener "the art of securing efficient operation"-L. Couffignal "the art of steersmanship"; "deals with all forms of behavior in so far as they are

regular, or determinate, or reproducible"; "stands to the real machine-electronic, mechanical, neural, or economic-much as geometry stands to a real object in our terrestrial space"; "offers a method for the scientific treatment of the system in which complexity is outstanding and too important to be ignored"-W. Ross Ashby

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Block I, Unit 1 Cybernetics

Cybernetics: definitions “a branch of mathematics dealing with problems of control, recursiveness, and

information"-Gregory Bateson "the science of effective organization"-Stafford Beer "the art and science of manipulating defensible metaphors"-Gordon Pask "Should one name one central concept, a first principle, of cybernetics, it would

be circularity."-Heinz von Foerster "a way of thinking"-Ernst von Glasersfeld "the science and art of understanding"-Humberto Maturana "Cybernetics: when I reflect on the dynamics of observed systems and on the

dynamics of the observer-whence 'creative cybernetics': when I project the dynamics of a system I would like to observe"-from announcement of 1987 ASC conference in Urbana-Champaign, Illinois

"the ability to cure all temporary truth of eternal triteness"-Herbert Brun

source: GWU

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Block I, Unit 1 Cybernetics

cybernetics attempts to find the common elements in the functioning of automatic machines and of the human nervous system, and to develop a theory that will cover the entire field of control and communication in machines and in living organisms.

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Block I, Unit 1 Cybernetics

The goal is to construct machines that have the following features:

Use of language Forming and using concepts Complex problem-solving, such as playing

chess Learning Creativity

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Block I, Unit 1 Symbolic AI

Intelligent machines: Search: capable to locate the answer to a problem by

sifting all possible answers and select the correct (or the best) one

Symbols and rules: can manipulate words (symbols) according to logical and linguistic rules

Mathematical structure: the implemented model must be a logical or mathematical structure of some kind.

Randomness: injection some degree of randomness into the orderly processes

Neuron Networks: simulating the structure found in the human brain

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Block I, Unit 1 Symbolic AI

Intelligent machines, two important keys: Representation: intelligent computer systems contain a

model in some logical or mathematical form, of the problem being solved. These models are thus essentially symbolic, consisting of logical expressions

Search: computer systems can find “intelligent” answers to complex problems by searching among all possible answers for the best one. The process of search will be governed by rules.

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Block I, Unit 1 Symbolic AI

What is Intelligence ? The ability to comprehend, to understand and to profit

from experience A general mental capability that involves the ability to

reason, plan, solve problems, think abstractly, comprehend ideas and language and learn

The ability of an individual to understand and cope with the environment

The capacity to create constructively for the purpose of evolutionary gain

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Block I, Unit 1 Intelligence

Observations Observation 1 : There is an obvious lack of agreement on

what intelligence is, and thus of the exact goals of artificial intelligence.

Observation 2 : The only really clear and effective definitions of intelligence are in terms of a few examples of intelligent behavior: perception, reasoning and action, in the case of Winston above; decision making, problem solving and learning in Bellman’s definition.

Observation 3 : The overwhelming focus is on human intelligence.

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Block I, Unit 1 Intelligence

Alain Turing (1912, 1954) the father of AI Code breaker during the second world war Turing machine (invented on paper, 1936), it consists of:

a read/write head (or 'scanner') with a paper tape passing through it

The tape is divided into squares, each square bearing a single symbol

This tape is the machine's general purpose storage medium, serving both as the vehicle for input and output and as a working memory for storing the results of intermediate steps of the computation.

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Block I, Turing work

The machine can: read (i.e. identify) the symbol currently under the head write a symbol on the square currently under the head

(after first deleting the symbol already written there, if any)

move the tape left one square move the tape right one square change state halt.

Turing test

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Block I, Turing work

Weak AI: computer value is that it gives us a very powerful tool.

Strong AI: computer is not only a tool, rather, the appropriately programmed computer really is a mind

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Block I, Unit 1 Cybernetics Vs. Symbolic AI

The digital computers Formal systems:

Taken States/starting state Rules

Automatic formal system: one that works by itself Deterministic Non deterministic Heuristics: experience based techniques for problem

solving

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Block I, Unit 1 Computers

What computers can do? Models, for a natural system we have:

Simulation: is a model that captures the functional connections between inputs and outputs of the system

Replication: is a model that captures the functional connections between inputs and outputs of the system and is based on processes that are same as, or similar to, those of the real-world-system

Emulation: is a model that captures the functional connections between inputs and outputs of the system and is based on processes that are same as, or similar to, those of the real-world-system and in the same materials as the natural system.

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Block I, Unit 1 Computers

Optimization problems: Traveling Salesman Problem (TSP):

For 5 cities, 120 possible combinations For 10 cities, 3.628.800 combinations For 15 cities, 1.307.674.368.000 combinations For 20 cities, 2.43 1018

Combinatorial explosion TSP is an NP hard problem. (there is no known algorithm

for solving it in any realistic period of time, although such algorithm may exist)

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Block I, Unit 1 Computers