Automated Slovene crosswords solving with the help of the internet

The goal of the thesis was to create a program, that automatically solves Slovene crosswords with the help of puzzle dictionary and web search. For the purpose of creating the program, we used a database of 367 crosswords and puzzle dictionary with 104.123 clue answers. We also created a list of web answers for all the crosswords in the database. Because of the enormous amount of the web answers searching the whole solution space would not be feasible. That is why the program solves each crossword in two separate phases. In the first phase, a crossword gets partially solved with the help of the puzzle dictionary, which creates a list of most probable solution candidates for each clue. In the second phase, a crossword is solved with puzzle dictionary and web answers combined. For the purpose of building the program, we used a set of 37 training crosswords. The final results were obtained from a set of 330 testing crosswords

Crossword Construction using Constraint Satisfaction and Simulated Annealing

Selle töö eesmärk on luua programm, mis koostab ristsõnu, kasutades kahte meetodit: kitsenduste rahuldamist (KR) ahne algoritmiga ja libalõõmutamist (LL), ning võrrelda nende meetodite efektiivsust. Tööd hakatakse kasutama õppematerjalina aine Tehisintellekt I õpetamisel. Ristsõna koostamine on üks tehisintellekti probleemidest, mis kuulub NP-täielike klassi. Seega hea lahenduse leidmine nõuab palju ressursse ja aega. Aga eksisteerivad meetodid, mis võimaldavad lahenduse leidmise aega vähendada. Nende hulgas on ka KR ja LL. KR kasutades seatakse antud ülesandele kitsendusi, mis teevad lahendamise lihtsamaks. Ristsõna koostamisel kehtivad järgmised kitsendused: 1.Sõna ei saa olla lühem, kui ruutude järjend, kuhu seda pannakse. 2.Sõna ei saa olla pikem, kui ruutude järjend, kuhu seda pannakse. 3.Kui järjendis on mõned tähed juba olemas, siis sõna, mis pannakse sellesse järjendisse, peab neid tähti sisaldama täpselt nendel samadel positsioonidel ja ei saa sisaldada mingeid teisi tähti nendel positsioonidel. Kui sõna rahuldab neid tingimusi, siis teda võetakse vastu ning ahne algoritm otsustab, kasutades heuristilist funktsiooni, kas see sõna on parim lahendus selles olukorras.Niiviisi püüab programm lõpliku sammude hulgaga optimaalse lahenduseni jõuda. LL töötab nii: antud on suvaline algseisund s, leida tema naaberseisund s', kui uus seisund on jooksvast seisundist parem, siis valida see, aga kui leitud seisund on jooksvast seisundist halvem, siis kasutada tõenäosus funktsiooni P, et otsustada, kas valida seda seisundit või mitte. Sellist operatsiooni korratakse kuni rahuldav lahendus on leitud või algoritm on juba teinud lubatud arvu samme. Tõenäosus, et algoritm valib uueks seisundiks halvema seisundi väheneb aja jooksul (kooskõlas nn temperatuuri alanemisega). Meetodeid on testitud ja võrreldid, kasutades erinevaid heuristikuid.The main goal of this thesis is to create a program that allows constructing crosswords, using two different algorithms. Given a grid and a text file with words (dictionary), the program should search for suitable words from a dictionary to fill the grid. The program should be able to complete this task in two different ways, in this case using constraint satisfaction method (CSM) with greedy algorithm and simulated annealing. Afore-mentioned algorithms were chosen mainly for educational purposes, since construction of the fastest algorithm is not a goal of this work. Along with other similar Artificial Intelligence problems, like N queens problem, map colouring and Sudoku solving (which is also NP-complete problem), crossword construction is a good example of simple, yet nontrivial task. The choice of CSM with greedy algorithm is obvious. If there are no constraints, the program will simply try to fill each entry by placing up to all, and that means also the words that are of inappropriate length, words in vocabulary until it finds first suitable or runs out of words. For example, by putting constraints on words length and already filled letters, the construction time can be drastically reduced. The simulated annealing was chosen with intention to show that the same problem can be solved in different ways and also to illustrate the difference in algorithm processing and its effectiveness. In addition, simulated annealing is quite similar to greedy algorithm, thus making their comparison a bit easier, but more interesting

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

A Survey of Monte Carlo Tree Search Methods

Monte Carlo tree search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling. It has received considerable interest due to its spectacular success in the difficult problem of computer Go, but has also proved beneficial in a range of other domains. This paper is a survey of the literature to date, intended to provide a snapshot of the state of the art after the first five years of MCTS research. We outline the core algorithm's derivation, impart some structure on the many variations and enhancements that have been proposed, and summarize the results from the key game and nongame domains to which MCTS methods have been applied. A number of open research questions indicate that the field is ripe for future work

Towards 40 years of constraint reasoning

Research on constraints started in the early 1970s. We are approaching 40 years since the beginning of this successful field, and it is an opportunity to revise what has been reached. This paper is a personal view of the accomplishments in this field. We summarize the main achievements along three dimensions: constraint solving, modelling and programming. We devote special attention to constraint solving, covering popular topics such as search, inference (especially arc consistency), combination of search and inference, symmetry exploitation, global constraints and extensions to the classical model. For space reasons, several topics have been deliberately omitted.Partially supported by the Spanish project TIN2009-13591-C02-02 and Generalitat de Catalunya grant 2009-SGR-1434.Peer Reviewe

Applied Cognitive Sciences

Cognitive science is an interdisciplinary field in the study of the mind and intelligence. The term cognition refers to a variety of mental processes, including perception, problem solving, learning, decision making, language use, and emotional experience. The basis of the cognitive sciences is the contribution of philosophy and computing to the study of cognition. Computing is very important in the study of cognition because computer-aided research helps to develop mental processes, and computers are used to test scientific hypotheses about mental organization and functioning. This book provides a platform for reviewing these disciplines and presenting cognitive research as a separate discipline

Born free and equal?: on the ethical consistency of animal equality

This dissertation investigates the possibility of constructing a consistent ethical system that offers clear notions of equality and incorporates an animal ethic. The first part is more meta-ethical in nature, reflecting on notions such as moral intuitions, universalism, consistency and coherence. It demonstrates that moral illusions might exist and offers a method to discover such moral illusions. The second part turns to normative ethics, dealing with principles of welfare, justice and basic rights. It tackles problems ranging from population ethics to non-ideal theory. Finally, the third part moves to applied (animal) ethics, In analogy to optical illusions, I demonstrate that speciesism is not only a kind of prejudicial discrimination but also a moral illusion: an obstinate intuitive judgment that is inconsistent with a coherent system. The third part also tackles the predation problem and the sentience problem in animal ethics. The end result of this work is a pluralist principlist ethical system that can be captured in a metaphor of five moral fingers working together as the moral hand. This moral hand is a constructed, coherent ethical system of five universalized ethical principles based on strong moral intuitions. The thumb represents the principle of universalism, which is a basic ingredient of coherentism, and generates an anti-discrimination rule. The index finger symbolizes a consequentialist welfare ethic, based on the coherence of impartiality and empathy. The middle finger is the mere means principle of a deontological rights ethic: humans (and animals) have a right not to be used as merely means to someone else’s ends. This principle captures a lot of moral intuitions that pop up in famous dilemmas. A fourth principle, the ring finger, refers to the value of biodiversity and adopts some elements of carnism, the opposite of veganism as ideology. This fourth principle solves the predation problem and is coherent with some other moral intuitions. Finally, the little finger represents the principle of tolerated partiality which can be used in some final moral dilemmas. With these five fingers of ethics, we can grasp the moral problem of consuming animal products, and answer the question whether veganism is a moral duty

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion