Solving colored nonograms

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia InformáticaIn this thesis we deepen the study of colored nonogram solving using Integer Linear Programming(ILP). The known methods for solving this kind of problems are the depth-first search(brute-force) one, the iterative one and the ILP one. Our approach generalizes the one used by Robert A. Bosch which was developed for black and white nonograms only, thus providing a new universal solution for solving nonograms using ILP. Since the iterative implementations are the ones that present better performance results, we also developed a hybrid method that combines this approach and the ILP one. These puzzles often have more than one solution. The way to find them using the iterative method is to make a tree search with backtracking. In order to find the remaining solutions using our approach, it is necessary to apply an algorithm that uses a binary cut to exclude already known solutions. In order to perform comparative tests between approaches, we developed a nonogram generator that allows us to define the resolution of the puzzle, its number of colors and its density(number of painted cells vs. resolution). Finally we compare the performance of our approach in solving colored nonograms against the iterative one

Symphony. Alleviating depression symptoms through science based video gaming

A depressão representa um grande encargo econômico na Europa e em todo o mundo, é esperado que se torne a segunda doença mental mais comum em todo o mundo até 2020. Os tratamentos de primeira linha incluem medicação e psicoterapia, os quais podem produzir efeitos colaterais indesejáveis, ou serem ineficazes por várias razões que vão da escassez de profissionais treinados, até ao desconforto dos pacientes com os resultados. Terapias alternativas, como a música e terapias baseadas em tecnologia, têm sido propostas como tratamentos alternativos. Esta tese propõe o uso de um jogo casual afim de ajudar pessoas com sintomatologia depressiva. Foi realizado um estudo inicial com uma amostra de indivíduos com sintomas de depressão, leve a moderada, para entender a sua relação com videojogos, tendências de jogos e qual o tipo preferido de jogos. Concluímos que jogando no seu tempo livre, sozinhos e num computador ou dispositivo móvel tiveram maior preferência. Com base na informação coletada, criamos um jogo para dispositivos móveis chamado Symphony, baseado em resolver puzzles e audição musical, como meio de fornecer dicas para o bem-estar mental. Tentamos também promover a estimulação cognitiva, a melhoria de humor, e estratégias de regulação de emoções. Um teste de usabilidade foi realizado com 5 indivíduos da população geral para testar sua jogabilidade, onde eles preencheram questionários pré e pós-intervenção para avaliar seu humor e perceção do jogo. Uma experiência final foi realizada com uma amostra da população-alvo de 8 voluntários, que também completaram questionários pré e pós-intervenção para avaliar o impacto de jogar Symphony em seus níveis de depressão, humor e também para conhecer sua perceção do jogo. Os dados dos questionários e os comentários e observações informais dos terapeutas, revelaram respostas emocionais positivas e mudanças de humor resultantes de jogar Symphony. As quais, sugerem melhorias para tornar Symphony mais eficaz e adaptável a cada indivíduo.Depression is a heavy economic burden in Europe and worldwide, and it is expected to reach second place as the most common mental illness worldwide by 2020. First-line treatments include medication and psychotherapy, but they may either bring undesirable side-effects or be ineffective for several reasons that go from the shortage of trained practitioners to lack of compliance. Alternative therapies, such as music and technology based therapies, have been proposed as adjunctive treatments. This thesis proposes using a casual-game to aid people with depressive symptomatology. We conducted an initial study with a sample of individuals with mild to moderate depression symptoms to understand their regards to video-games, gaming tendencies, and preferred type of games. Playing in their free time, alone and on a computer or mobile device were mostly preferred, so we created a mobile casual game called Symphony based on puzzle-playing and music-listening to give tips for their mental well-being, promote cognitive stimulation, mood improvement, and emotion regulation strategies. A usability test conducted with 5 individuals from the general population was conducted to test its playability, where they completed pre- and post-intervention questionnaires to assess their mood and perception of the game. A final experiment was conducted with a sample of the target population of 8 volunteers, who also completed pre- and post-intervention questionnaires to assess the impact of playing Symphony on their depression levels, mood, and also to gather their perception of the game. Questionnaire data and therapists’ informal comments and observations reveal overall positive emotional responses and mood changes resulting from playing Symphony, and suggest improvements to make Symphony more effective and adaptable to each individual

Exploiting Game Decompositions in Monte Carlo Tree Search

International audienceIn this paper, we propose a variation of the MCTS framework to perform a search in several trees to exploit game decompositions. Our Multiple Tree MCTS (MT-MCTS) approach builds simultaneously multiple MCTS trees corresponding to the different sub-games and allows , like MCTS algorithms, to evaluate moves while playing. We apply MT-MCTS on decomposed games in the General Game Playing framework. We present encouraging results on single player games showing that this approach is promising and opens new avenues for further research in the domain of decomposition exploitation. Complex compound games are solved from 2 times faster (Incredible) up to 25 times faster (Nonogram)

Logic Programming Applications: What Are the Abstractions and Implementations?

This article presents an overview of applications of logic programming, classifying them based on the abstractions and implementations of logic languages that support the applications. The three key abstractions are join, recursion, and constraint. Their essential implementations are for-loops, fixed points, and backtracking, respectively. The corresponding kinds of applications are database queries, inductive analysis, and combinatorial search, respectively. We also discuss language extensions and programming paradigms, summarize example application problems by application areas, and touch on example systems that support variants of the abstractions with different implementations

Exploiting Global Constraints for Search and Propagation

Résumé Cette thèse se concentre sur la Programmation par contraintes (PPC), qui est un paradigme émergent pour résoudre des problèmes complexes d’optimisation combinatoire. Les principales contributions tournent autour du filtrage des contraintes et de la recherche; les deux sont des composantes cl´e dans la résolution de problèmes complexes à travers la PPC. D’un côté, le filtrage des contraintes permet de réduire la taille de l’espace de recherche, d’autre part, la recherche définit la manière dont cet espace sera exploré. Les progrès sur ces sujets sont essentiels pour élargir l’applicabilité de CP à des problèmes réels. En ce qui concerne le filtrage des contraintes, les contributions sont les suivantes: premièrement, on propose une amélioration sur un algorithme existant de la version relaxée d’une contrainte commune qui apparaît souvent dans les problèmes d’affectation (soft gcc). L’algorithme proposé améliore en termes de complexité soit pour la cohérence, soit pour le filtrage et en termes de facilité d’implémentation. Deuxièmement, on introduit une nouvelle contrainte (soit dure soit relaxée) et les algorithmes de filtrage pour une sous-structure récurrente qui se produit dans les problèmes d’affectation des ressources hétérogènes (hierarchical gcc). Nous montrons des résultats encourageants par rapport à une d´écomposition équivalente basée sur gcc. En ce qui concerne la recherche, nous présentons tout d’abord les algorithmes pour compter le nombre de solutions pour deux importantes familles de contraintes: les contraintes sur les occurrences, par exemple, alldifferent, symmetric alldifferent et gcc, et les contraintes de séquence admissible, telles que regular. Ces algorithmes sont à la base d’une nouvelle famille d’heuristiques de recherche, centrées sur les contraintes et basées sur le d´énombrement. Ces heuristiques extraient des informations sur le nombre de solutions des contraintes, pour guider la recherche vers des parties de l’espace de recherche qui contiennent probablement un grand nombre de solutions. Les résultats expérimentaux sur huit différents problèmes montrent une performance impressionnante par rapport à l’état de l’art des heuristiques génériques. Enfin, nous expérimentons une forme forte, déjà connue, de filtrage qui est guidée par la recherche (quick shaving). Cette technique donne des résultats soit encourageants soit mauvais lorsqu’elle est appliquée aveuglément à tous les problèmes. Nous avons introduit un estimateur simple mais très efficace pour activer ou désactiver dynamiquement le quick shaving; de tests expérimentaux ont montré des résultats très prometteurs.----------Abstract This thesis focuses on Constraint Programming (CP), that is an emergent paradigm to solve complex combinatorial optimization problems. The main contributions revolve around constraint filtering and search that are two main components of CP. On one side, constraint filtering allows to reduce the size of the search space, on the other, search defines how this space will be explored. Advances on these topics are crucial to broaden the applicability of CP to real-life problems. For what concerns constraint filtering, the contribution is twofold: we firstly propose an improvement on an existing algorithm of the relaxed version of a constraint that frequently appears in assignment problems (soft gcc). The algorithm proposed outperforms the previously known in terms of time-complexity both for the consistency check and for the filtering and in term of ease of implementiation. Secondly, we introduce a new constraint (both hard and soft version) and associated filtering algorithms for a recurrent sub-structure that occurs in assignment problems with heterogeneous resources (hierarchical gcc). We show promising results when compared to an equivalent decomposition based on gcc. For what concerns search, we introduce algorithms to count the number of solutions for two important families of constraints: occurrence counting constraints, such as alldifferent, symmetric alldifferent and gcc, and sequencing constraints, such as regular. These algorithms are the building blocks of a new family of search heuristics, called constraint-centered counting-based heuristics. They extract information about the number of solutions the individual constraints admit, to guide search towards parts of the search space that are likely to contain a high number of solutions. Experimental results on eight different problems show an impressive performance compared to other generic state-of-the-art heuristics. Finally, we experiment on an already known strong form of constraint filtering that is heuristically guided by the search (quick shaving). This technique gives mixed results when applied blindly to any problem. We introduced a simple yet very effective estimator to dynamically disable quick shaving and showed experimentally very promising results

An improved image steganography scheme based on distinction grade value and secret message encryption

Steganography is an emerging and greatly demanding technique for secure information communication over the internet using a secret cover object. It can be used for a wide range of applications such as safe circulation of secret data in intelligence, industry, health care, habitat, online voting, mobile banking and military. Commonly, digital images are used as covers for the steganography owing to their redundancy in the representation, making them hidden to the intruders, hackers, adversaries, unauthorized users. Still, any steganography system launched over the Internet can be cracked upon recognizing the stego cover. Thus, the undetectability that involves data imperceptibility or concealment and security is the significant trait of any steganography system. Presently, the design and development of an effective image steganography system are facing several challenges including low capacity, poor robustness and imperceptibility. To surmount such limitations, it is important to improve the capacity and security of the steganography system while maintaining a high signal-to-noise ratio (PSNR). Based on these factors, this study is aimed to design and develop a distinction grade value (DGV) method to effectively embed the secret data into a cover image for achieving a robust steganography scheme. The design and implementation of the proposed scheme involved three phases. First, a new encryption method called the shuffle the segments of secret message (SSSM) was incorporated with an enhanced Huffman compression algorithm to improve the text security and payload capacity of the scheme. Second, the Fibonacci-based image transformation decomposition method was used to extend the pixel's bit from 8 to 12 for improving the robustness of the scheme. Third, an improved embedding method was utilized by integrating a random block/pixel selection with the DGV and implicit secret key generation for enhancing the imperceptibility of the scheme. The performance of the proposed scheme was assessed experimentally to determine the imperceptibility, security, robustness and capacity. The standard USC-SIPI images dataset were used as the benchmarking for the performance evaluation and comparison of the proposed scheme with the previous works. The resistance of the proposed scheme was tested against the statistical, X2 , Histogram and non-structural steganalysis detection attacks. The obtained PSNR values revealed the accomplishment of higher imperceptibility and security by the proposed DGV scheme while a higher capacity compared to previous works. In short, the proposed steganography scheme outperformed the commercially available data hiding schemes, thereby resolved the existing issues