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Parity Games: Descriptive Complexity and Algorithms for New Solvers
Imperial College London Department of Computing Parity Games: Descriptive Complexity and Algorithms for New Solvers Huan-Pu Kuo 2013 Supervised by Prof Michael Huth, and Dr Nir Piterman Submitted in part fulfilment of the requirements for the degree of Doctor of Philosophy in Computing of Imperial College London and the Diploma of Imperial College London 1 Declaration I herewith certify that all material in this dissertation which is not my own work has been duly acknowledged. Selected results from this dissertation have been disseminated in scientific publications detailed in Chapter 1.4. Huan-Pu Kuo 2 Copyright Declaration The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work. 3 Abstract Parity games are 2-person, 0-sum, graph-based, and determined games that form an important foundational concept in formal methods (see e.g., [Zie98]), and their exact computational complexity has been an open prob- lem for over twenty years now. In this thesis, we study algorithms that solve parity games in that they determine which nodes are won by which player, and where such decisions are supported with winning strategies. We modify and so improve a known algorithm but also propose new algorithmic approaches to solving parity games and to understanding their descriptive complexity. -
On Variations of Nim and Chomp Arxiv:1705.06774V1 [Math.CO] 18
On Variations of Nim and Chomp June Ahn Benjamin Chen Richard Chen Ezra Erives Jeremy Fleming Michael Gerovitch Tejas Gopalakrishna Tanya Khovanova Neil Malur Nastia Polina Poonam Sahoo Abstract We study two variations of Nim and Chomp which we call Mono- tonic Nim and Diet Chomp. In Monotonic Nim the moves are the same as in Nim, but the positions are non-decreasing numbers as in Chomp. Diet-Chomp is a variation of Chomp, where the total number of squares removed is limited. 1 Introduction We study finite impartial games with two players where the same moves are available to both players. Players alternate moves. In a normal play, the person who does not have a move loses. In a misère play, the person who makes the last move loses. A P-position is a position from which the previous player wins, assuming perfect play. We can observe that all terminal positions are P-positions. An N-position is a position from which the next player wins given perfect play. When we play we want to end our move with a P-position and want to see arXiv:1705.06774v1 [math.CO] 18 May 2017 an N-position before our move. Every impartial game is equivalent to a Nim heap of a certain size. Thus, every game can be assigned a non-negative integer, called a nimber, nim- value, or a Grundy number. The game of Nim is played on several heaps of tokens. A move consists of taking some tokens from one of the heaps. The game of Chomp is played on a rectangular m by n chocolate bar with grid lines dividing the bar into mn squares. -
Learning Board Game Rules from an Instruction Manual Chad Mills A
Learning Board Game Rules from an Instruction Manual Chad Mills A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science University of Washington 2013 Committee: Gina-Anne Levow Fei Xia Program Authorized to Offer Degree: Linguistics – Computational Linguistics ©Copyright 2013 Chad Mills University of Washington Abstract Learning Board Game Rules from an Instruction Manual Chad Mills Chair of the Supervisory Committee: Professor Gina-Anne Levow Department of Linguistics Board game rulebooks offer a convenient scenario for extracting a systematic logical structure from a passage of text since the mechanisms by which board game pieces interact must be fully specified in the rulebook and outside world knowledge is irrelevant to gameplay. A representation was proposed for representing a game’s rules with a tree structure of logically-connected rules, and this problem was shown to be one of a generalized class of problems in mapping text to a hierarchical, logical structure. Then a keyword-based entity- and relation-extraction system was proposed for mapping rulebook text into the corresponding logical representation, which achieved an f-measure of 11% with a high recall but very low precision, due in part to many statements in the rulebook offering strategic advice or elaboration and causing spurious rules to be proposed based on keyword matches. The keyword-based approach was compared to a machine learning approach, and the former dominated with nearly twenty times better precision at the same level of recall. This was due to the large number of rule classes to extract and the relatively small data set given this is a new problem area and all data had to be manually annotated. -
The Switch Operators and Push-The-Button Games: a Sequential Compound Over Rulesets
The switch operators and push-the-button games: a sequential compound over rulesets Eric Duchêne1, Marc Heinrich1, Urban Larsson2, and Aline Parreau1 1Université Lyon 1, LIRIS, UMR5205, France∗ 2The Faculty of Industrial Engineering and Management, Technion - Israel Institute of Technology, Israel December 22, 2017 Abstract We study operators that combine combinatorial games. This field was initiated by Sprague- Grundy (1930s), Milnor (1950s) and Berlekamp-Conway-Guy (1970-80s) via the now classical disjunctive sum operator on (abstract) games. The new class consists in operators for rulesets, dubbed the switch-operators. The ordered pair of rulesets (R1; R2) is compatible if, given any position in R1, there is a description of how to move in R2. Given compatible (R1; R2), we build the push-the-button game R1 } R2, where players start by playing according to the rules R1, but at some point during play, one of the players must switch the rules to R2, by pushing the button ‘}’. Thus, the game ends according to the terminal condition of ruleset R2. We study the pairwise combinations of the classical rulesets Nim, Wythoff and Euclid. In addition, we prove that standard periodicity results for Subtraction games transfer to this setting, and we give partial results for a variation of Domineering, where R1 is the game where the players put the domino tiles horizontally and R2 the game where they play vertically (thus generalizing the octal game 0.07). Keywords: Combinatorial game; Ruleset compound; Nim; Wythoff Nim; Euclid’s game; 1 Gallimaufry–new combinations of games Combinatorial Game Theory (CGT) concerns combinations of individual games. -
Remembering Frank Harary
Discrete Mathematics Letters Discrete Math. Lett. 6 (2021) 1–7 www.dmlett.com DOI: 10.47443/dml.2021.s101 Editorial Remembering Frank Harary On March 11, 2005, at a special session of the 36th Southeastern International Conference on Combinatorics, Graph The- ory, and Computing held at Florida Atlantic University in Boca Raton, the famous mathematician Ralph Stanton, known for his work in combinatorics and founder of the Institute of Combinatorics and Its Applications, stated that the three mathematicians who had the greatest impact on modern graph theory have now all passed away. Stanton was referring to Frenchman Claude Berge of France, Canadian William Tutte, originally from England, and a third mathematician, an American, who had died only 66 days earlier and to whom this special session was being dedicated. Indeed, that day, March 11, 2005, would have been his 84th birthday. This third mathematician was Frank Harary. Let’s see what led Harary to be so recognized by Stanton. Frank Harary was born in New York City on March 11, 1921. He was the oldest child of Jewish immigrants from Syria and Russia. He earned a B.A. degree from Brooklyn College in 1941, spent a graduate year at Princeton University from 1943 to 1944 in theoretical physics, earned an M.A. degree from Brooklyn College in 1945, spent a year at New York University from 1945 to 1946 in applied mathematics, and then moved to the University of California at Berkeley, where he wrote his Ph.D. Thesis on The Structure of Boolean-like Rings, in 1949, under Alfred Foster. -
Impartial Games
Combinatorial Games MSRI Publications Volume 29, 1995 Impartial Games RICHARD K. GUY In memory of Jack Kenyon, 1935-08-26 to 1994-09-19 Abstract. We give examples and some general results about impartial games, those in which both players are allowed the same moves at any given time. 1. Introduction We continue our introduction to combinatorial games with a survey of im- partial games. Most of this material can also be found in WW [Berlekamp et al. 1982], particularly pp. 81{116, and in ONAG [Conway 1976], particu- larly pp. 112{130. An elementary introduction is given in [Guy 1989]; see also [Fraenkel 1996], pp. ??{?? in this volume. An impartial game is one in which the set of Left options is the same as the set of Right options. We've noticed in the preceding article the impartial games = 0=0; 0 0 = 1= and 0; 0; = 2: {|} ∗ { | } ∗ ∗ { ∗| ∗} ∗ that were born on days 0, 1, and 2, respectively, so it should come as no surprise that on day n the game n = 0; 1; 2;:::; (n 1) 0; 1; 2;:::; (n 1) ∗ {∗ ∗ ∗ ∗ − |∗ ∗ ∗ ∗ − } is born. In fact any game of the type a; b; c;::: a; b; c;::: {∗ ∗ ∗ |∗ ∗ ∗ } has value m,wherem =mex a;b;c;::: , the least nonnegative integer not in ∗ { } the set a;b;c;::: . To see this, notice that any option, a say, for which a>m, { } ∗ This is a slightly revised reprint of the article of the same name that appeared in Combi- natorial Games, Proceedings of Symposia in Applied Mathematics, Vol. 43, 1991. Permission for use courtesy of the American Mathematical Society. -
Complexity in Simulation Gaming
Complexity in Simulation Gaming Marcin Wardaszko Kozminski University [email protected] ABSTRACT The paper offers another look at the complexity in simulation game design and implementation. Although, the topic is not new or undiscovered the growing volatility of socio-economic environments and changes to the way we design simulation games nowadays call for better research and design methods. The aim of this article is to look into the current state of understanding complexity in simulation gaming and put it in the context of learning with and through complexity. Nature and understanding of complexity is both field specific and interdisciplinary at the same time. Analyzing understanding and role of complexity in different fields associated with simulation game design and implementation. Thoughtful theoretical analysis has been applied in order to deconstruct the complexity theory and reconstruct it further as higher order models. This paper offers an interdisciplinary look at the role and place of complexity from two perspectives. The first perspective is knowledge building and dissemination about complexity in simulation gaming. Second, perspective is the role the complexity plays in building and implementation of the simulation gaming as a design process. In the last section, the author offers a new look at the complexity of the simulation game itself and perceived complexity from the player perspective. INTRODUCTION Complexity in simulation gaming is not a new or undiscussed subject, but there is still a lot to discuss when it comes to the role and place of complexity in simulation gaming. In recent years, there has been a big number of publications targeting this problem from different perspectives and backgrounds, thus contributing to the matter in many valuable ways. -
(November 12-13)- Page 545
College Park Program (October 30-31) - Page 531 Baton Rouge Program (November 12-13)- Page 545 Notices of the American Mathematical Society < 2.. c: 3 ('1) ~ z c: 3 C" ..,('1) 0'1 October 1982, Issue 220 Volume 29, Number 6, Pages 497-616 Providence, Rhode Island USA ISSN 0002-9920 Calendar of AMS Meetings THIS CALENDAR lists all meetings which have been approved by the Council prior to the date this issue of the Notices was sent to press. The summer and annual meetings are joint meetings of the Mathematical Association of America and the Ameri· can Mathematical Society. The meeting dates which fall rather far in the future are subject to change; this is particularly true of meetings to which no numbers have yet been assigned. Programs of the meetings will appear in the issues indicated below. First and second announcements of the meetings will have appeared in earlier issues. ABSTRACTS OF PAPERS presented at a meeting of the Society are published in the journal Abstracts of papers presented to the American Mathematical Society in the issue corresponding to that of the Notices which contains the program of the meet· ing. Abstracts should be submitred on special forms which are available in many departments of mathematics and from the office of the Society in Providence. Abstracts of papers to be presented at the meeting must be received at the headquarters of the Society in Providence, Rhode Island, on or before the deadline given below for the meeting. Note that the deadline for ab· stracts submitted for consideration for presentation at special sessions is usually three weeks earlier than that specified below. -
Combinatorial Game Theory
Combinatorial Game Theory Aaron N. Siegel Graduate Studies MR1EXLIQEXMGW Volume 146 %QIVMGER1EXLIQEXMGEP7SGMIX] Combinatorial Game Theory https://doi.org/10.1090//gsm/146 Combinatorial Game Theory Aaron N. Siegel Graduate Studies in Mathematics Volume 146 American Mathematical Society Providence, Rhode Island EDITORIAL COMMITTEE David Cox (Chair) Daniel S. Freed Rafe Mazzeo Gigliola Staffilani 2010 Mathematics Subject Classification. Primary 91A46. For additional information and updates on this book, visit www.ams.org/bookpages/gsm-146 Library of Congress Cataloging-in-Publication Data Siegel, Aaron N., 1977– Combinatorial game theory / Aaron N. Siegel. pages cm. — (Graduate studies in mathematics ; volume 146) Includes bibliographical references and index. ISBN 978-0-8218-5190-6 (alk. paper) 1. Game theory. 2. Combinatorial analysis. I. Title. QA269.S5735 2013 519.3—dc23 2012043675 Copying and reprinting. Individual readers of this publication, and nonprofit libraries acting for them, are permitted to make fair use of the material, such as to copy a chapter for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary acknowledgment of the source is given. Republication, systematic copying, or multiple reproduction of any material in this publication is permitted only under license from the American Mathematical Society. Requests for such permission should be addressed to the Acquisitions Department, American Mathematical Society, 201 Charles Street, Providence, Rhode Island 02904-2294 USA. Requests can also be made by e-mail to [email protected]. c 2013 by the American Mathematical Society. All rights reserved. The American Mathematical Society retains all rights except those granted to the United States Government. -
Decompositions and Graceful Labelings (Supplemental Material for Intro to Graph Theory)
Decompositions and Graceful Labelings (Supplemental Material for Intro to Graph Theory) Robert A. Beeler∗ December 17, 2015 1 Introduction A graph decomposition is a particular problem in the field of combinatorial designs (see Wallis [22] for more information on design theory). A graph decomposition of a graph H is a partition of the edge set of H. In this case, the graph H is called the host for the decomposition. Most graph decomposition problems are concerned with the case where every part of the partition is isomorphic to a single graph G. In this case, we refer to the graph G as the prototype for the decomposition. Further, we refer to the parts of the partition as blocks. As an example, consider the host graph Q3 as shown in Figure 1. In this case, we want to find a decomposition of Q3 into isomorphic copies of the path on three vertices, P3. We label the vertices of P3 as an ordered triple (a, b, c). where ab and bc are the edges of P3. The required blocks in the decompositions are (0, 2, 4), (1, 0, 6), (1, 3, 2), (1, 7, 5), (3, 5, 4), and (4, 6, 7). Usually, the goal of a combinatorial design is to determine whether the particular design is possible. The same is true for graph decompositions. Namely, given a host graph H and a prototype G, determine whether there exist a decomposition of H into isomorphic copies of G. Often, this is a difficult problem. In fact, there are entire books written on the subject (for ∗Department of Mathematics and Statistics, East Tennessee State University, Johnson City, TN 37614-1700 USA email: [email protected] 1 2 0 1 2 3 4 5 6 7 Figure 1: A P3-decomposition of a Q3 example, see Bos´ak [1] and Diestel [5]). -
Mathematics Throughout the Ages. II
Mathematics throughout the ages. II Helena Durnová A history of discrete optimalization In: Eduard Fuchs (editor): Mathematics throughout the ages. II. (English). Praha: Výzkumné centrum pro dějiny vědy, 2004. pp. 51–184. Persistent URL: http://dml.cz/dmlcz/401175 Terms of use: © Jednota českých matematiků a fyziků Institute of Mathematics of the Czech Academy of Sciences provides access to digitized documents strictly for personal use. Each copy of any part of this document must contain these Terms of use. This document has been digitized, optimized for electronic delivery and stamped with digital signature within the project DML-CZ: The Czech Digital Mathematics Library http://dml.cz MATHEMATICS THROUGHOUT THE AGES II A History of Discrete Optimization Helena Durnová PRAGUE 2004 This is a Ph.D. thesis written under the supervision of Prof. Eduard Fuchs, defended at the Department of Mathematics of the Faculty of Science of Masaryk University in Brno on 24st May 2001. Contents 1 Introduction 57 1.1 Optimality and Mathematics . 58 1.2 GraphTheory......................... 64 1.3 ObjectivesoftheThesis . 69 2 Mathematical Background 71 2.1 Basic Definitions in Graph Theory . 71 2.1.1 Directed and undirected graphs . 71 2.1.2 Weighted graphs . 74 2.1.3 Description of graphs . 75 2.2 Algorithms, Heuristics, Complexity . 77 2.2.1 Algorithms and heuristics . 77 2.2.2 Complexity ...................... 78 3 Shortest Path Problem 81 3.1 SpecificBackground . 82 3.2 Origins and Development of Shortest Path Problems . 83 3.3 Early Shortest Path Algorithms . 85 3.3.1 Shimbel,1954. .. .. .. .. .. 85 3.3.2 G. B. -
Game Complexity Vs Strategic Depth
Game Complexity vs Strategic Depth Matthew Stephenson, Diego Perez-Liebana, Mark Nelson, Ahmed Khalifa, and Alexander Zook The notion of complexity and strategic depth within games has been a long- debated topic with many unanswered questions. How exactly do you measure the complexity of a game? How do you quantify its strategic depth objectively? This seminar answered neither of these questions but instead presents the opinion that these properties are, for the most part, subjective to the human or agent that is playing them. What is complex or deep for one player may be simple or shallow for another. Despite this, determining generally applicable measures for estimating the complexity and depth of a given game (either independently or comparatively), relative to the abilities of a given player or player type, can provide several benefits for game designers and researchers. There are multiple possible ways of measuring the complexity or depth of a game, each of which is likely to give a different outcome. Lantz et al. propose that strategic depth is an objective, measurable property of a game, and that games with a large amount of strategic depth continually produce challenging problems even after many hours of play [1]. Snakes and ladders can be described as having no strategic depth, due to the fact that each player's choices (or lack thereof) have no impact on the game's outcome. Other similar (albeit subjective) evaluations are also possible for some games when comparing relative depth, such as comparing Tic-Tac-Toe against StarCraft. However, these comparative decisions are not always obvious and are often biased by personal preference.