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Commit efbb8e1c authored by M. Chardon's avatar M. Chardon
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alea - aide générale

parent c3c21878
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<p>
Randomness is a mathematical notion that is used in many
modern life area. It is use in the form of a random sequence
in geolocalisation system, automatic gambling games, cryptology
and others. The mathematical definition of a ransom sequence
is still going under discussions, but certain properties
have been demonstrated and an agreement was found around three approaches:
</p>
<ul>
<li>The frequency, measure-theoretic approach (Martin-Löf, 1966) (No random sequence should have exceptional regularity or be effectively testable).</li>
<li>The complexity, compressibility approach (Chaitin 1975) (A random sequence should be incompressible)</li>
<li>The predictability approach (Schnorr 1971) (A random sequence should be unpredictable)</li>
</ul>
<p>
From there, no random sequence can be generated from an
algorithm. If so, the sequence will be considered as pseudorandom
and its level of randomness will depend from the context.
</p>
<p>
The sources of randomness can be separated into three
categories: unpredictable (dices, random sorting,…),
physical (radioactivity, electromagnetism,…), computational
(mix of physic and algorithms).
</p>
<p>
Another potential way is the human brain. Human decision
have been showed to be influenced by bias, but few studies
have been made on the human capacity to produce a random
sequence. To do so, the experience will ask the user
to write a sequence of numbers and to play with it,
the aim being to fool the computer.
</p>
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<p>
L’aléatoire est une notion mathématique utile à plusieurs secteurs de la vie moderne. Elle est entre autres retrouvée dans les systèmes de géolocalisation, dans les jeux de hasard informatisés et en cryptologie sous la forme de suites de nombres aléatoires. La définition mathématique d’une suite aléatoire est encore de nos jours ouverte aux débats. Certaines propriétés ont néanmoins pu être démontrées, et un certain consensus formé autour de trois définitions :
</p>
<ul>
<li>« Une suite aléatoire ne doit posséder aucune régularité exceptionnelle et effectivement testable » (Martin-Löf 1966)</li>
<li>« Une suite aléatoire doit posséder un contenu informationnel incompressible » (Levin 1974, Chaitin 1975)</li>
<li>« Une suite aléatoire doit être imprévisible, c’est-à-dire qu’aucune stratégie effective ne peut mener un gain infini si l’on parie sur les termes de la suite » (Schnorr 1971)</li>
</ul>
<p>
Ainsi, toute suite dite aléatoire ne peut être décrite ou générée par un algorithme. Si c’est le cas, la suite sera classée comme suite pseudo-aléatoire et son caractère aléatoire dépendra de l’entropie demandée par le contexte.
</p>
<p>
Les phénomènes permettant une génération ont été rassemblés en trois catégories : les phénomènes imprévisibles (dés, tirage au sort,..), les phénomènes physiques (radioactivité, bruits électromagnétiques, …) et des générateurs mixtes qui mêlent les phénomènes susmentionnés à des algorithmes.
</p>
<p>
Un quatrième moyen potentiel est le cerveau humain. Il a déjà été montré que les décisions humaines sont fortement liées à plusieurs types de biais, mais peu d’études se sont intéressées à la capacité humaine de produire une suite de nombres de manière aléatoire et à mesurer cette entropie.
Pour se faire, il sera demandé à l’opérateur d’écrire une suite de chiffres tirés aléatoirement puis de jouer avec afin d’essayer d’être le moins prévisible possible.
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<html xml:lang="en" xmlns="http://www.w3.org/1999/xhtml">
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<meta name="keywords" content="Cipher, Bigdata, Guess" />
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<p>
Randomness is a mathematical notion that is used in many
modern life area. It is use in the form of a random sequence
in geolocalisation system, automatic gambling games, cryptology
and others. The mathematical definition of a ransom sequence
is still going under discussions, but certain properties
have been demonstrated and an agreement was found around three approaches:
</p>
<ul>
<li>The frequency, measure-theoretic approach (Martin-Löf, 1966) (No random sequence should have exceptional regularity or be effectively testable).</li>
<li>The complexity, compressibility approach (Chaitin 1975) (A random sequence should be incompressible)</li>
<li>The predictability approach (Schnorr 1971) (A random sequence should be unpredictable)</li>
</ul>
<p>
From there, no random sequence can be generated from an
algorithm. If so, the sequence will be considered as pseudorandom
and its level of randomness will depend from the context.
</p>
<p>
The sources of randomness can be separated into three
categories: unpredictable (dices, random sorting,…),
physical (radioactivity, electromagnetism,…), computational
(mix of physic and algorithms).
</p>
<p>
Another potential way is the human brain. Human decision
have been showed to be influenced by bias, but few studies
have been made on the human capacity to produce a random
sequence. To do so, the experience will ask the user
to write a sequence of numbers and to play with it,
the aim being to fool the computer.
</p>
</div>
</div>
</div>
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......@@ -48,7 +48,7 @@
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