Nested Monte Carlo Tree Search as Applied to Samurai Sudoku

As Sudoku has come into prominence as a favorite logic puzzle, mathematicians and computer scientists alike have analyzed the game for interesting properties. The large search space presents a challenge for both generating and solving Sudoku puzzles without relying on techniques that simply permute a valid puzzle. These permutations result in puzzles that are essentially the same since they follow the same solution path. Many Sudoku generating or solving programs rely on brute-force methods to avoid this pitfall, but this is inefficient since there is no heuristic to navigate the huge search space. A nested Monte Carlo tree search has some basis in brute-force methods, but guides the search in order to achieve better results by using random games within nested search stages. In this paper, we show that when the nested Monte Carlo search algorithm is implemented for solving Samurai Sudoku, a version of Sudoku in which a standard Sudoku puzzle is placed with four other standard Sudoku puzzles overlapping on each of the corners, it performs better than a completely random brute-force algorithm. Additionally, an improvement to the nested Monte Carlo search is made by implementing a heuristic that is used at each level of search

Physical Zero-Knowledge Proofs for Akari, Takuzu, Kakuro and KenKen

Akari, Takuzu, Kakuro and KenKen are logic games similar to Sudoku. In Akari, a labyrinth on a grid has to be lit by placing lanterns, respecting various constraints. In Takuzu a grid has to be filled with 0's and 1's, while respecting certain constraints. In Kakuro a grid has to be filled with numbers such that the sums per row and column match given values; similarly in KenKen a grid has to be filled with numbers such that in given areas the product, sum, difference or quotient equals a given value. We give physical algorithms to realize zero-knowledge proofs for these games which allow a player to show that he knows a solution without revealing it. These interactive proofs can be realized with simple office material as they only rely on cards and envelopes. Moreover, we formalize our algorithms and prove their security.Comment: FUN with algorithms 2016, Jun 2016, La Maddalena, Ital

Solving Sudoku with Ant Colony Optimization

In this paper we present a new algorithm for the well-known and computationally-challenging Sudoku puzzle game. Our Ant Colony Optimization-based method significantly out-performs the state-of-the-art algorithm on the hardest, large instances of Sudoku. We provide evidence that – compared to traditional backtracking methods – our algorithm offers a much more efficient search of the solution space, and demonstrate the utility of a novel anti-stagnation operator. This work lays the foundation for future work on a general-purpose puzzle solver, and establishes Japanese pencil puzzles as a suitable platform for benchmarking a wide range of algorithms

Comparison of Sudoku Solving Skills of Preschool Children Enrolled in the Montessori Approach and the National Education Programs Yıldız Güven1, Cihat Gültekin1, A. Beyzanur Dedeoğlu1

According to Johnson-Laird (2010), sudoku, a mind game, is based on a pure deduction and reasoning processes. This study analyzed sudoku solving skills of preschool children and to ascertain whether there was a difference between children who were educated according to the Ministry of Education preschool education program and the Montessori approach. Sudoku skills of children were analyzed by gender, age, duration of preschool attendance, mother’s and father’s education level and previous experience of playing sudoku using a 12-question Sudoku Skills Measurement Tool developed for this research study.The study sample of the study consisted of 118 children (57 girls, 61 boys) aged between 54-77 months. The findings showed that there was no significant difference in sudoku skills by gender. However, sudoku skills varied with age (54-65 months and 66-77 months) in favor of older groups. Children's sudoku skills were more developed with an increase in education level of either parent. Children who had been in preschool for longer had higher sudoku scores. A previous experience of playing sudoku did not impact sudoku scores. Sudoku skills of children who were educated according to the Montessori program were more developed compared to those of children educated according to Ministry of National Education program

J-POP: Japanese Puzzles as Optimization Problems

Japanese puzzle games such as Sudoku and Futoshiki are familiar recreational pursuits, but they also present an interesting computational challenge. A number of algorithms exist for the automated solution of such puzzles, but, until now, these have not been compared in a unified way. Here we present an integrated framework for the study of combinatorial black-box optimisation, using Japanese puzzles as the test-bed. Importantly, our platform is extendable, allowing for the easy addition of both puzzles and solvers. We compare the performance of a number of optimization algorithms on six different puzzle games, and identify a subset of puzzle instances that could provide a challenging benchmark set for future algorithms

USING COGNITIVE WORD GAMES TO PROMOTE LEXICAL MEMORY ACCESS AND VOCABULARY RETRIEVAL IN SECOND LANGUAGE LEARNERS

Fluency in a second language (L2) is one of the most important skills for the modern world. However, adults learning a new language face many obstacles, including motivation, time, and other challenges in learning. Technology learning tools may help solve these problems. In this dissertation, I tested the effectiveness of cognitive word games as a vocabulary learning method, with the main goal of investigating how different word games including a crossword paradigm task, a free association task and a word-stem completion task were effective at improving vocabulary memory access. The games selectively increased semantic (meaning) or orthographic (spelling) associations in an English lexicon, which may lead to improved access and usage of L2 vocabulary. Three experiments were conducted. Experiment 1 examined lexical memory and recognition/retrieval processes in native English speakers. The results showed a significant effect of the game conditions on response times of a lexical association task, such that the most effective training game was the free association task. Experiment 2 was designed to probe the same game effectiveness with non-native English speakers. This time, the findings indicated significant effects of the training games on correct responses of the lexical association task and response times of a new anagram solving task. Experiment 3 was designed to investigate the game effectiveness on comprehensive English reading test scores. The results suggested that after a week of training, the games failed to improve learners\u27 performance on the English reading scores. However, training methods differed in how much the learners improved during the practice, with crossword practice leading to large improvements and word stem completion getting worse, indicating differences in engagement and in-task language learning. In addition, feedback from participants revealed that some of them enjoyed the games, especially the crossword paradigm task. In summary, these studies provided a broad understanding of using the word games to enhance English vocabulary skills. The games can be used for further lexical investigations or adapted for classroom purposes

Dagstuhl Reports : Volume 1, Issue 2, February 2011

Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn

Some Enhancement Methods For Backtracking-Search In Solving Multiple Permutation Problems

In this dissertation, we present some enhancement methods for backtracking-search in solving multiple permutation problems. Some well-known NP-complete multiple permutation problems are Quasigroup Completion Problem and Sudoku. Multiple permutation problems have been getting a lot of attention in the literature in the recent years due to having a highly structured nature and being a challenging combinatorial search problem. Furthermore, it has been shown that many real-world problems in scheduling and experimental design take the form of multiple permutation problems. Therefore, it has been suggested that they can be used as a benchmark problem to test various enhancement methods for solving constraint satisfaction problems. Then it is hoped that the insight gained from studying them can be applied to other hard structured as well as unstructured problems. Our supplementary and novel enhancement methods for backtracking-search in solving these multiple permutation problems can be summarized as follows: We came up with a novel way to encode multiple permutation problems and then we designed and developed an arc-consistency algorithm that is tailored towards this modeling. We implemented five versions of this arc-consistency algorithm where the last version eliminates almost all of the possible propagation redundancy. Then we introduced the novel notion of interlinking dynamic variable ordering with dynamic value ordering, where the dynamic value ordering is also used as a second tie-breaker for the dynamic variable ordering. We also proposed the concept of integrating dynamic variable ordering and dynamic value ordering into an arc-consistency algorithm by using greedy counting assertions. We developed the concept of enforcing local-consistency between variables from different redundant models of the problem. Finally, we introduced an embarrassingly parallel task distribution process at the beginning of the search. We theoretically proved that the limited form of the Hall\u27s theorem is enforced by our modeling of the multiple permutation problems. We showed with our empirical results that the ``fail-first principle is confirmed in terms of minimizing the total number of explored nodes, but is refuted in terms of minimizing the depth of the search tree when finding a single solution, which correlates with previously published results. We further showed that the performance (total number instances solved at the phase transition point within a given time limit) of a given search heuristic is closely related to the underlying pruning algorithm that is being employed to maintain some level of local-consistency during backtracking-search. We also extended the previously established hypothesis, which stated that the second peak of hardness for NP-complete problems is algorithm dependent, to second peak of hardness for NP-complete problems is also search-heuristic dependent. Then we showed with our empirical results that several of our enhancement methods on backtracking-search perform better than the constraint solvers MAC-LAH and Minion as well as the SAT solvers Satz and MiniSat for previously tested instances of multiple permutation problems on these solvers