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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. -
An Very Brief Overview of Surreal Numbers for Gandalf MM 2014
An very brief overview of Surreal Numbers for Gandalf MM 2014 Steven Charlton 1 History and Introduction Surreal numbers were created by John Horton Conway (of Game of Life fame), as a greatly simplified construction of an earlier object (Alling’s ordered field associated to the class of all ordinals, as constructed via modified Hahn series). The name surreal numbers was coined by Donald Knuth (of TEX and the Art of Computer Programming fame) in his novel ‘Surreal Numbers’ [2], where the idea was first presented. Surreal numbers form an ordered Field (Field with a capital F since surreal numbers aren’t a set but a class), and are in some sense the largest possible ordered Field. All other ordered fields, rationals, reals, rational functions, Levi-Civita field, Laurent series, superreals, hyperreals, . , can be found as subfields of the surreals. The definition/construction of surreal numbers leads to a system where we can talk about and deal with infinite and infinitesimal numbers as naturally and consistently as any ‘ordinary’ number. In fact it let’s can deal with even more ‘wonderful’ expressions 1 √ 1 ∞ − 1, ∞, ∞, ,... 2 ∞ in exactly the same way1. One large area where surreal numbers (or a slight generalisation of them) finds application is in the study and analysis of combinatorial games, and game theory. Conway discusses this in detail in his book ‘On Numbers and Games’ [1]. 2 Basic Definitions All surreal numbers are constructed iteratively out of two basic definitions. This is an wonderful illustration on how a huge amount of structure can arise from very simple origins. -
An Introduction to Conway's Games and Numbers
AN INTRODUCTION TO CONWAY’S GAMES AND NUMBERS DIERK SCHLEICHER AND MICHAEL STOLL 1. Combinatorial Game Theory Combinatorial Game Theory is a fascinating and rich theory, based on a simple and intuitive recursive definition of games, which yields a very rich algebraic struc- ture: games can be added and subtracted in a very natural way, forming an abelian GROUP (§ 2). There is a distinguished sub-GROUP of games called numbers which can also be multiplied and which form a FIELD (§ 3): this field contains both the real numbers (§ 3.2) and the ordinal numbers (§ 4) (in fact, Conway’s definition gen- eralizes both Dedekind sections and von Neumann’s definition of ordinal numbers). All Conway numbers can be interpreted as games which can actually be played in a natural way; in some sense, if a game is identified as a number, then it is under- stood well enough so that it would be boring to actually play it (§ 5). Conway’s theory is deeply satisfying from a theoretical point of view, and at the same time it has useful applications to specific games such as Go [Go]. There is a beautiful microcosmos of numbers and games which are infinitesimally close to zero (§ 6), and the theory contains the classical and complete Sprague-Grundy theory on impartial games (§ 7). The theory was founded by John H. Conway in the 1970’s. Classical references are the wonderful books On Numbers and Games [ONAG] by Conway, and Win- ning Ways by Berlekamp, Conway and Guy [WW]; they have recently appeared in their second editions. -
Arxiv:2101.07237V2 [Cs.CC] 19 Jan 2021 Ohtedsg N Oprtv Nlsso Obntra Games
TRANSVERSE WAVE: AN IMPARTIAL COLOR-PROPAGATION GAME INSPRIED BY SOCIAL INFLUENCE AND QUANTUM NIM Kyle Burke Department of Computer Science, Plymouth State University, Plymouth, New Hampshire, https://turing.plymouth.edu/~kgb1013/ Matthew Ferland Department of Computer Science, University of Southern California, Los Angeles, California, United States Shang-Hua Teng1 Department of Computer Science, University of Southern California, Los Angeles, California, United States https://viterbi-web.usc.edu/~shanghua/ Abstract In this paper, we study a colorful, impartial combinatorial game played on a two- dimensional grid, Transverse Wave. We are drawn to this game because of its apparent simplicity, contrasting intractability, and intrinsic connection to two other combinatorial games, one inspired by social influence and another inspired by quan- tum superpositions. More precisely, we show that Transverse Wave is at the intersection of social-influence-inspired Friend Circle and superposition-based Demi-Quantum Nim. Transverse Wave is also connected with Schaefer’s logic game Avoid True. In addition to analyzing the mathematical structures and com- putational complexity of Transverse Wave, we provide a web-based version of the game, playable at https://turing.plymouth.edu/~kgb1013/DB/combGames/transverseWave.html. Furthermore, we formulate a basic network-influence inspired game, called Demo- graphic Influence, which simultaneously generalizes Node-Kyles and Demi- arXiv:2101.07237v2 [cs.CC] 19 Jan 2021 Quantum Nim (which in turn contains as special cases Nim, Avoid True, and Transverse Wave.). These connections illuminate the lattice order, induced by special-case/generalization relationships over mathematical games, fundamental to both the design and comparative analyses of combinatorial games. 1Supported by the Simons Investigator Award for fundamental & curiosity-driven research and NSF grant CCF1815254. -
Alpha-Beta Pruning
Alpha-Beta Pruning Carl Felstiner May 9, 2019 Abstract This paper serves as an introduction to the ways computers are built to play games. We implement the basic minimax algorithm and expand on it by finding ways to reduce the portion of the game tree that must be generated to find the best move. We tested our algorithms on ordinary Tic-Tac-Toe, Hex, and 3-D Tic-Tac-Toe. With our algorithms, we were able to find the best opening move in Tic-Tac-Toe by only generating 0.34% of the nodes in the game tree. We also explored some mathematical features of Hex and provided proofs of them. 1 Introduction Building computers to play board games has been a focus for mathematicians ever since computers were invented. The first computer to beat a human opponent in chess was built in 1956, and towards the late 1960s, computers were already beating chess players of low-medium skill.[1] Now, it is generally recognized that computers can beat even the most accomplished grandmaster. Computers build a tree of different possibilities for the game and then work backwards to find the move that will give the computer the best outcome. Al- though computers can evaluate board positions very quickly, in a game like chess where there are over 10120 possible board configurations it is impossible for a computer to search through the entire tree. The challenge for the computer is then to find ways to avoid searching in certain parts of the tree. Humans also look ahead a certain number of moves when playing a game, but experienced players already know of certain theories and strategies that tell them which parts of the tree to look. -
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. -
Combinatorial Game Theory Théorie Des Jeux Combinatoires (Org
Combinatorial Game Theory Théorie des jeux combinatoires (Org: Melissa Huggan (Ryerson), Svenja Huntemann (Concordia University of Edmonton) and/et Richard Nowakowski (Dalhousie)) ALEXANDER CLOW, St. Francis Xavier University Red, Blue, Green Poset Games This talk examines Red, Blue, Green (partizan) poset games under normal play. Poset games are played on a poset where players take turns choosing an element of the partial order and removing every element greater than or equal to it in the ordering. The Left player can choose Blue elements (Right cannot) and the Right player can choose Red elements (while the Left cannot) and both players can choose Green elements. Red, Blue and Red, Blue, Green poset games have not seen much attention in the literature, do to most questions about Green poset games (such as CHOMP) remaining open. We focus on results that are true of all Poset games, but time allowing, FENCES, the poset game played on fences (or zig-zag posets) will be considered. This is joint work with Dr.Neil McKay. MATTHIEU DUFOUR AND SILVIA HEUBACH, UQAM & California State University Los Angeles Circular Nim CN(7,4) Circular Nim CN(n; k) is a variation on Nim. A move consists of selecting k consecutive stacks from n stacks arranged in a circle, and then to remove at least one token (and as many as all tokens) from the selected stacks. We will briefly review known results on Circular Nim CN(n; k) for small values of n and k and for some families, and then discuss new features that have arisen in the set of the P-positions of CN(7,4). -
Algorithmic Combinatorial Game Theory∗
Playing Games with Algorithms: Algorithmic Combinatorial Game Theory∗ Erik D. Demaine† Robert A. Hearn‡ Abstract Combinatorial games lead to several interesting, clean problems in algorithms and complexity theory, many of which remain open. The purpose of this paper is to provide an overview of the area to encourage further research. In particular, we begin with general background in Combinatorial Game Theory, which analyzes ideal play in perfect-information games, and Constraint Logic, which provides a framework for showing hardness. Then we survey results about the complexity of determining ideal play in these games, and the related problems of solving puzzles, in terms of both polynomial-time algorithms and computational intractability results. Our review of background and survey of algorithmic results are by no means complete, but should serve as a useful primer. 1 Introduction Many classic games are known to be computationally intractable (assuming P 6= NP): one-player puzzles are often NP-complete (as in Minesweeper) or PSPACE-complete (as in Rush Hour), and two-player games are often PSPACE-complete (as in Othello) or EXPTIME-complete (as in Check- ers, Chess, and Go). Surprisingly, many seemingly simple puzzles and games are also hard. Other results are positive, proving that some games can be played optimally in polynomial time. In some cases, particularly with one-player puzzles, the computationally tractable games are still interesting for humans to play. We begin by reviewing some basics of Combinatorial Game Theory in Section 2, which gives tools for designing algorithms, followed by reviewing the relatively new theory of Constraint Logic in Section 3, which gives tools for proving hardness. -
COMPSCI 575/MATH 513 Combinatorics and Graph Theory
COMPSCI 575/MATH 513 Combinatorics and Graph Theory Lecture #34: Partisan Games (from Conway, On Numbers and Games and Berlekamp, Conway, and Guy, Winning Ways) David Mix Barrington 9 December 2016 Partisan Games • Conway's Game Theory • Hackenbush and Domineering • Four Types of Games and an Order • Some Games are Numbers • Values of Numbers • Single-Stalk Hackenbush • Some Domineering Examples Conway’s Game Theory • J. H. Conway introduced his combinatorial game theory in his 1976 book On Numbers and Games or ONAG. Researchers in the area are sometimes called onagers. • Another resource is the book Winning Ways by Berlekamp, Conway, and Guy. Conway’s Game Theory • Games, like everything else in the theory, are defined recursively. A game consists of a set of left options, each a game, and a set of right options, each a game. • The base of the recursion is the zero game, with no options for either player. • Last time we saw non-partisan games, where each player had the same options from each position. Today we look at partisan games. Hackenbush • Hackenbush is a game where the position is a diagram with red and blue edges, connected in at least one place to the “ground”. • A move is to delete an edge, a blue one for Left and a red one for Right. • Edges disconnected from the ground disappear. As usual, a player who cannot move loses. Hackenbush • From this first position, Right is going to win, because Left cannot prevent him from killing both the ground supports. It doesn’t matter who moves first. -
On Numbers, Germs, and Transseries
On Numbers, Germs, and Transseries Matthias Aschenbrenner, Lou van den Dries, Joris van der Hoeven Abstract Germs of real-valued functions, surreal numbers, and transseries are three ways to enrich the real continuum by infinitesimal and infinite quantities. Each of these comes with naturally interacting notions of ordering and deriva- tive. The category of H-fields provides a common framework for the relevant algebraic structures. We give an exposition of our results on the model theory of H-fields, and we report on recent progress in unifying germs, surreal num- bers, and transseries from the point of view of asymptotic differential algebra. Contemporaneous with Cantor's work in the 1870s but less well-known, P. du Bois- Reymond [10]{[15] had original ideas concerning non-Cantorian infinitely large and small quantities [34]. He developed a \calculus of infinities” to deal with the growth rates of functions of one real variable, representing their \potential infinity" by an \actual infinite” quantity. The reciprocal of a function tending to infinity is one which tends to zero, hence represents an \actual infinitesimal”. These ideas were unwelcome to Cantor [39] and misunderstood by him, but were made rigorous by F. Hausdorff [46]{[48] and G. H. Hardy [42]{[45]. Hausdorff firmly grounded du Bois-Reymond's \orders of infinity" in Cantor's set-theoretic universe [38], while Hardy focused on their differential aspects and introduced the logarithmico-exponential functions (short: LE-functions). This led to the concept of a Hardy field (Bourbaki [22]), developed further mainly by Rosenlicht [63]{[67] and Boshernitzan [18]{[21]. For the role of Hardy fields in o-minimality see [61]. -
ES.268 Dynamic Programming with Impartial Games, Course Notes 3
ES.268 , Lecture 3 , Feb 16, 2010 http://erikdemaine.org/papers/AlgGameTheory_GONC3 Playing Games with Algorithms: { most games are hard to play well: { Chess is EXPTIME-complete: { n × n board, arbitrary position { need exponential (cn) time to find a winning move (if there is one) { also: as hard as all games (problems) that need exponential time { Checkers is EXPTIME-complete: ) Chess & Checkers are the \same" computationally: solving one solves the other (PSPACE-complete if draw after poly. moves) { Shogi (Japanese chess) is EXPTIME-complete { Japanese Go is EXPTIME-complete { U. S. Go might be harder { Othello is PSPACE-complete: { conjecture requires exponential time, but not sure (implied by P 6= NP) { can solve some games fast: in \polynomial time" (mostly 1D) Kayles: [Dudeney 1908] (n bowling pins) { move = hit one or two adjacent pins { last player to move wins (normal play) Let's play! 1 First-player win: SYMMETRY STRATEGY { move to split into two equal halves (1 pin if odd, 2 if even) { whatever opponent does, do same in other half (Kn + Kn = 0 ::: just like Nim) Impartial game, so Sprague-Grundy Theory says Kayles ≡ Nim somehow { followers(Kn) = fKi + Kn−i−1;Ki + Kn−i−2 j i = 0; 1; :::;n − 2g ) nimber(Kn) = mexfnimber(Ki + Kn−i−1); nimber(Ki + Kn−i−2) j i = 0; 1; :::;n − 2g { nimber(x + y) = nimber(x) ⊕ nimber(y) ) nimber(Kn) = mexfnimber(Ki) ⊕ nimber(Kn−i−1); nimber(Ki) ⊕ nimber(Kn−i−2) j i = 0; 1; :::n − 2g RECURRENCE! | write what you want in terms of smaller things Howe do w compute it? nimber(K0) = 0 (BASE CASE) nimber(K1) = mexfnimber(K0) ⊕ nimber(K0)g 0 ⊕ 0 = 0 = 1 nimber(K2) = mexfnimber(K0) ⊕ nimber(K1); 0 ⊕ 1 = 1 nimber(K0) ⊕ nimber(K0)g 0 ⊕ 0 = 0 = 2 so e.g. -
Blue-Red Hackenbush
Basic rules Two players: Blue and Red. Perfect information. Players move alternately. First player unable to move loses. The game must terminate. Mathematical Games – p. 1 Outcomes (assuming perfect play) Blue wins (whoever moves first): G > 0 Red wins (whoever moves first): G < 0 Mover loses: G = 0 Mover wins: G0 Mathematical Games – p. 2 Two elegant classes of games number game: always disadvantageous to move (so never G0) impartial game: same moves always available to each player Mathematical Games – p. 3 Blue-Red Hackenbush ground prototypical number game: Blue-Red Hackenbush: A player removes one edge of his or her color. Any edges not connected to the ground are also removed. First person unable to move loses. Mathematical Games – p. 4 An example Mathematical Games – p. 5 A Hackenbush sum Let G be a Blue-Red Hackenbush position (or any game). Recall: Blue wins: G > 0 Red wins: G < 0 Mover loses: G = 0 G H G + H Mathematical Games – p. 6 A Hackenbush value value (to Blue): 3 1 3 −2 −3 sum: 2 (Blue is two moves ahead), G> 0 3 2 −2 −2 −1 sum: 0 (mover loses), G= 0 Mathematical Games – p. 7 1/2 value = ? G clearly >0: Blue wins mover loses! x + x - 1 = 0, so x = 1/2 Blue is 1/2 move ahead in G. Mathematical Games – p. 8 Another position What about ? Mathematical Games – p. 9 Another position What about ? Clearly G< 0. Mathematical Games – p. 9 −13/8 8x + 13 = 0 (mover loses!) x = -13/8 Mathematical Games – p.