The Exploration and Analysis of Mancala from an AI Perspective

Through the study of popular games such as Chess and Go, countless artificial intelligence (AI) research has been conducted in an attempt to create algorithms equipped for adversarial search problems. However, there are still a plethora of avenues that offer insight into further development. Mancala is traditionally a two-player board game that originated in the East and offers a unique opponent-based playing experience. This thesis not only attempts to create a competitive AI algorithm for mancala games by analyzing the performance of several different algorithms on this classic board game, but it also attempts to extract applications that may have relevance to other “game-solving” AI problems

Review of Kalah Game research and the proposition of a novel heuristic-deterministic algorithm compared to tree-search solutions and human decision-making

The Kalah game represents the most popular version of probably the oldest board game ever-the Mancala game. From this viewpoint, the art of playing Kalah can contribute to cultural heritage. This paper primarily focuses on a review of Kalah history and on a survey of research made so far for solving and analyzing the Kalah game (and some other related Mancala games). This review concludes that even if strong in-depth tree-search solutions for some types of the game were already published, it is still reasonable to develop less time-consumptive and computationally-demanding playing algorithms and their strategies Therefore, the paper also presents an original heuristic algorithm based on particular deterministic strategies arising from the analysis of the game rules. Standard and modified mini-max tree-search algorithms are introduced as well. A simple C++ application with Qt framework is developed to perform the algorithm verification and comparative experiments. Two sets of benchmark tests are made; namely, a tournament where a mid-experienced amateur human player competes with the three algorithms is introduced first. Then, a round-robin tournament of all the algorithms is presented. It can be deduced that the proposed heuristic algorithm has comparable success to the human player and to low-depth tree-search solutions. Moreover, multiple-case experiments proved that the opening move has a decisive impact on winning or losing. Namely, if the computer plays first, the human opponent cannot beat it. Contrariwise, if it starts to play second, using the heuristic algorithm, it nearly always loses. © 2020 by the authors.European Regional Development FundEuropean Union (EU); Ministry of Education, Youth and SportsMinistry of Education, Youth & Sports - Czech Republic [LO1303 (MSMT-7778/2014)]; internal grant agency of VSB Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science, Czech Republic [SP2020/46

Meta Concepts: A Knowledge-Based Code Generation System

People have an amazing ability to solve complex problems by performing a sequence of simpler operations (i.e: functions/procedures which take input variables and produce output variables). We are able to do so even when there exists a large number of possible choices for such operations and when the number of combinatoric ways that these operations can be chained together is astronomical. On the other hand, computers typically do not solve problems this way and have to be programmed with a precise set of instructions. What is it that allows us to perform such a feat while computers cannot? One of the major features that sets us apart from computers is our ability to draw upon our large range of knowledge and its connections to the problem at hand. Meta Concepts aims to use knowledge-based information in this way to enable the automated generation of code in order to solve problems in cases where solutions would otherwise be difficult to devise by hand. Meta Concepts is an object-oriented coding system whereby the user specifies and works with an ontology of concepts or types/classes which captures knowledge about their usage and metadata about their methods, how method calls can be chained together, and associated method parameters and constraints. By augmenting the code generation process with knowledge-based information, the system is able to significantly narrow and prioritize its search through the otherwise vast search space in order to quickly generate high-performing solutions

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

Wythoff Wisdom

International audienceSix authors tell their stories from their encounters with the famous combinatorial game Wythoff Nim and its sequences, including a short survey on exactly covering systems

Games of History

Games of History provides an understanding of how games as artefacts, textual and visual sources on games and gaming as a pastime or a “serious” activity can be used as sources for the study of history. From the vast world of games, the book’s focus is on board and card games, with reference to physical games, sports and digital games as well. Considering culture, society, politics and metaphysics, the author uses examples from various places around the world and from ancient times to the present to demonstrate how games and gaming can offer the historian an alternative, often very valuable and sometimes unique path to the past. The book offers a thorough discussion of conceptual and material approaches to games as sources, while also providing the reader with a theoretical starting point for further study within specific thematic chapters. The book concludes with three case studies of different types of games and how they can be considered as historical sources: the gladiatorial games, chess and the digital game Civilization. Offering an alternative approach to the study of history through its focus on games and gaming as historical sources, this is the ideal volume for students considering different types of sources and how they can be used for historical study, as well as students who study games as primary or secondary sources in their history projects

Symbolic Search in Planning and General Game Playing

Search is an important topic in many areas of AI. Search problems often result in an immense number of states. This work addresses this by using a special datastructure, BDDs, which can represent large sets of states efficiently, often saving space compared to explicit representations. The first part is concerned with an analysis of the complexity of BDDs for some search problems, resulting in lower or upper bounds on BDD sizes for these. The second part is concerned with action planning, an area where the programmer does not know in advance what the search problem will look like. This part presents symbolic algorithms for finding optimal solutions for two different settings, classical and net-benefit planning, as well as several improvements to these algorithms. The resulting planner was able to win the International Planning Competition IPC 2008. The third part is concerned with general game playing, which is similar to planning in that the programmer does not know in advance what game will be played. This work proposes algorithms for instantiating the input and solving games symbolically. For playing, a hybrid player based on UCT and the solver is presented

Games of History

Games of History provides an understanding of how games as artefacts, textual and visual sources on games and gaming as a pastime or a “serious” activity can be used as sources for the study of history. From the vast world of games, the book’s focus is on board and card games, with reference to physical games, sports and digital games as well. Considering culture, society, politics and metaphysics, the author uses examples from various places around the world and from ancient times to the present to demonstrate how games and gaming can offer the historian an alternative, often very valuable and sometimes unique path to the past. The book offers a thorough discussion of conceptual and material approaches to games as sources, while also providing the reader with a theoretical starting point for further study within specific thematic chapters. The book concludes with three case studies of different types of games and how they can be considered as historical sources: the gladiatorial games, chess and the digital game Civilization. Offering an alternative approach to the study of history through its focus on games and gaming as historical sources, this is the ideal volume for students considering different types of sources and how they can be used for historical study, as well as students who study games as primary or secondary sources in their history projects