Effective player guidance in logic puzzles

Pen & paper puzzle games are an extremely popular pastime, often enjoyed by demographics normally not considered to be ‘gamers’. They are increasingly used as ‘serious games’ and there has been extensive research into computationally generating and efficiently solving them. However, there have been few academic studies that have focused on the players themselves. Presenting an appropriate level of challenge to a player is essential for both player enjoyment and engagement. Providing appropriate assistance is an essential mechanic for making a game accessible to a variety of players. In this thesis, we investigate how players solve Progressive Pen & Paper Puzzle Games (PPPPs) and how to provide meaningful assistance that allows players to recover from being stuck, while not reducing the challenge to trivial levels. This thesis begins with a qualitative in-person study of Sudoku solving. This study demonstrates that, in contrast to all existing assumptions used to model players, players were unsystematic, idiosyncratic and error-prone. We then designed an entirely new approach to providing assistance in PPPPs, which guides players towards easier deductions rather than, as current systems do, completing the next cell for them. We implemented a novel hint system using our design, with the assessment of the challenge being done using Minimal Unsatisfiable Sets (MUSs). We conducted four studies, using two different PPPPs, that evaluated the efficacy of the novel hint system compared to the current hint approach. The studies demonstrated that our novel hint system was as helpful as the existing system while also improving the player experience and feeling less like cheating. Players also chose to use our novel hint system significantly more often. We have provided a new approach to providing assistance to PPPP players and demonstrated that players prefer it over existing approaches

Using small MUSes to explain how to solve pen and paper puzzles

Pen and paper puzzles like Sudoku, Futoshiki and Skyscrapers are hugely popular. Solving such puzzles can be a trivial task for modern AI systems. However, most AI systems solve problems using a form of backtracking, while people try to avoid backtracking as much as possible. This means that existing AI systems do not output explanations about their reasoning that are meaningful to people. We present Demystify, a tool which allows puzzles to be expressed in a high-level constraint programming language and uses MUSes to allow us to produce descriptions of steps in the puzzle solving. We give several improvements to the existing techniques for solving puzzles with MUSes, which allow us to solve a range of significantly more complex puzzles and give higher quality explanations. We demonstrate the effectiveness and generality of Demystify by comparing its results to documented strategies for solving a range of pen and paper puzzles by hand, showing that our technique can find many of the same explanations.Publisher PD

Towards generic explanations for pen and paper puzzles with MUSes

This research was supported by the Royal Society URF\R\180015 .Pen and paper puzzles like Sudoku, Futoshiki and Star Battle are hugely popular. Solving such puzzles can be a trivial task for modern AI systems. However, most AI systems solve problems using a form of backtracking, while people try to avoid backtracking as much as possible. This means that existing AI systems do not output explanations about their reasoning that are meaningful to people. We present Demystify, a tool which allows puzzles to be expressed in a high-level constraint programming language and uses MUSes to allow us to produce descriptions of steps in the puzzle solving. We give several improvements to the existing techniques for solving puzzles with MUSes, which allow us to solve a range of significantly more complex puzzles and give higher quality explanations. We demonstrate the effectiveness and generality of Demystify by comparing its results to documented strategies for solving a range of pen and paper puzzles by hand, showing that our technique can find many of the same explanations.Publisher PD

Using Small MUSes to Explain How to Solve Pen and Paper Puzzles

In this paper, we present Demystify, a general tool for creating human-interpretable step-by-step explanations of how to solve a wide range of pen and paper puzzles from a high-level logical description. Demystify is based on Minimal Unsatisfiable Subsets (MUSes), which allow Demystify to solve puzzles as a series of logical deductions by identifying which parts of the puzzle are required to progress. This paper makes three contributions over previous work. First, we provide a generic input language, based on the Essence constraint language, which allows us to easily use MUSes to solve a much wider range of pen and paper puzzles. Second, we demonstrate that the explanations that Demystify produces match those provided by humans by comparing our results with those provided independently by puzzle experts on a range of puzzles. We compare Demystify to published guides for solving a range of different pen and paper puzzles and show that by using MUSes, Demystify produces solving strategies which closely match human-produced guides to solving those same puzzles (on average 89% of the time). Finally, we introduce a new randomised algorithm to find MUSes for more difficult puzzles. This algorithm is focused on optimised search for individual small MUSes

Attribution et variation du genre d'emprunts à l'anglais, à l'italien, au japonais et à l'arabe dans le lexique du français

Le genre des emprunts lexicaux référant à des entités non-sexuées en français est parfois considéré comme arbitraire, alors qu’il est parfois vu comme motivé par sa forme physique et/ou ses significations. Puisque les avis diffèrent à ce sujet, nous nous sommes intéressé à analyser de nombreux critères pouvant contribuer à l’attribution du genre d’un emprunt. Nous avons constitué quatre corpus, chacun composé de textes issus d’une communauté linguistique emprunteuse (Québec et Europe) et d’un niveau de formalité (formel ou informel). Nous avons observé que le genre des emprunts varie considérablement dans de nombreux cas. Nous constatons que les emprunts des langues à genre (italien, arabe) conservent généralement leur genre originel. Les critères sémantiques et de forme physique peuvent autant justifier le genre d’un emprunt l’un que l’autre. Le critère sémantique le plus opératoire intègre chaque emprunt dans un paradigme conceptuel regroupant plusieurs unités lexicales sous une même conceptualisation et, généralement, un genre commun au paradigme.Gender assignment to lexical non-human loanwords in French is not easily predictable. Some authors will consider it as arbitrary, others as motivated from physical or semantic properties of a given word. Because points of view on this matter are highly divided, we investigated and analysed many criteria that may contribute to gender assignment to loanwords in French. We compiled four corpora, each one composed of texts originating from one of two different linguistic communities (the province of Québec or Europe) and either a formal or informal context. We noticed that a loanword’s assigned gender varies considerably between usages in many cases. However, in general, loanwords from languages having a binary gender feature, such as Italian or Arabic, usually keep their original gender. Semantic criteria may justify loanword gender as much as physical criteria. The most productive semantic criterion is the conceptual paradigm into which the loanword is integrated, which groups together many lexical units under a similar conceptualisation, and usually a common gender