Hit Code : Optimitzant el mastermind per a dispositius mòbils

Hi ha diferents videojocs del mastermind arreu de les diferents plataformes, però no hi ha cap aplicació que permeti jugar al usuari contra la màquina i viceversa per a dispositius mòbil. En aquest projecte, s'analitzen diferents algorismes d'intel·ligència artificial per tal d'afrontar el repte d'elaborar un joc per a jugar al mastermind que ofereixi la possibilitat d'encertar el codi de l'usuari mitjançant algorismes, i que a l'hora sigui capaç de poder-se executar en un mòbil de gamma baixa amb sistema operatiu android per a fer-lo més accessible a la majoria dels usuaris.There are a lot of videogames for playing mastermind games throughout the diferent platforms, but there isn't any application that allows users the possibility to play against the computer and vice versa for mobile devices. This project analyze various artificial intelligence algorithms in order to face the challenge of develop a game to play mastermind offering the possibility of hitting the user code using algorithms, and at the same time, it was being able to run it on a low-end mobile with android operative system to make it more accessible to most users.Hay diferentes videojuegos del mastermind para muchas plataformas diferentes, pero no hay ninguna aplicación que permita jugar al usuario contra la máquina y viceversa para dispositivos móviles. En este proyecto, se analizan diferentes algoritmos de inteligencia artificial para afrontar el reto de elaborar un juego para jugar al mastermind que ofrezca la posibilidad de acertar el código del usuario mediante algoritmos, y que a la hora sea capaz de poderse ejecutar en un móvil de gama baja con sistema operativo android para hacerlo más accesible a la mayoría de los usuarios

Learning Character Strings via Mastermind Queries, with a Case Study Involving mtDNA

We study the degree to which a character string, $Q$, leaks details about itself any time it engages in comparison protocols with a strings provided by a querier, Bob, even if those protocols are cryptographically guaranteed to produce no additional information other than the scores that assess the degree to which $Q$ matches strings offered by Bob. We show that such scenarios allow Bob to play variants of the game of Mastermind with $Q$ so as to learn the complete identity of $Q$. We show that there are a number of efficient implementations for Bob to employ in these Mastermind attacks, depending on knowledge he has about the structure of $Q$, which show how quickly he can determine $Q$. Indeed, we show that Bob can discover $Q$ using a number of rounds of test comparisons that is much smaller than the length of $Q$, under reasonable assumptions regarding the types of scores that are returned by the cryptographic protocols and whether he can use knowledge about the distribution that $Q$ comes from. We also provide the results of a case study we performed on a database of mitochondrial DNA, showing the vulnerability of existing real-world DNA data to the Mastermind attack.Comment: Full version of related paper appearing in IEEE Symposium on Security and Privacy 2009, "The Mastermind Attack on Genomic Data." This version corrects the proofs of what are now Theorems 2 and 4

Exploring the space of human exploration using Entropy Mastermind

What drives people’s exploration in complex scenarios where they have to actively acquire information? How do people adapt their selection of queries to the environment? We explore these questions using Entropy Mastermind, a novel variant of the Mastermind code-breaking game, in which participants have to guess a secret code by making useful queries. Participants solved games more efficiently if the entropy of the game environment was low; moreover, people adapted their initial queries to the scenario they were in. We also investigated whether it would be possible to predict participants’ queries within the generalized Sharma-Mittal information-theoretic framework. Although predicting individual queries was difficult, the modeling framework offered important insights on human behavior. Entropy Mastermind opens up rich possibilities for modeling and behavioral research

Playing Mastermind With Constant-Size Memory

We analyze the classic board game of Mastermind with $n$ holes and a constant number of colors. A result of Chv\'atal (Combinatorica 3 (1983), 325-329) states that the codebreaker can find the secret code with $\Theta(n / \log n)$ questions. We show that this bound remains valid if the codebreaker may only store a constant number of guesses and answers. In addition to an intrinsic interest in this question, our result also disproves a conjecture of Droste, Jansen, and Wegener (Theory of Computing Systems 39 (2006), 525-544) on the memory-restricted black-box complexity of the OneMax function class.Comment: 23 page