Regular Boardgames

We propose a new General Game Playing (GGP) language called Regular Boardgames (RBG), which is based on the theory of regular languages. The objective of RBG is to join key properties as expressiveness, efficiency, and naturalness of the description in one GGP formalism, compensating certain drawbacks of the existing languages. This often makes RBG more suitable for various research and practical developments in GGP. While dedicated mostly for describing board games, RBG is universal for the class of all finite deterministic turn-based games with perfect information. We establish foundations of RBG, and analyze it theoretically and experimentally, focusing on the efficiency of reasoning. Regular Boardgames is the first GGP language that allows efficient encoding and playing games with complex rules and with large branching factor (e.g.\ amazons, arimaa, large chess variants, go, international checkers, paper soccer).Comment: AAAI 201

Games, puzzles, and computation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 147-153).There is a fundamental connection between the notions of game and of computation. At its most basic level, this is implied by any game complexity result, but the connection is deeper than this. One example is the concept of alternating nondeterminism, which is intimately connected with two-player games. In the first half of this thesis, I develop the idea of game as computation to a greater degree than has been done previously. I present a general family of games, called Constraint Logic, which is both mathematically simple and ideally suited for reductions to many actual board games. A deterministic version of Constraint Logic corresponds to a novel kind of logic circuit which is monotone and reversible. At the other end of the spectrum, I show that a multiplayer version of Constraint Logic is undecidable. That there are undecidable games using finite physical resources is philosophically important, and raises issues related to the Church-Turing thesis. In the second half of this thesis, I apply the Constraint Logic formalism to many actual games and puzzles, providing new hardness proofs. These applications include sliding-block puzzles, sliding-coin puzzles, plank puzzles, hinged polygon dissections, Amazons, Kohane, Cross Purposes, Tip over, and others.(cont.) Some of these have been well-known open problems for some time. For other games, including Minesweeper, the Warehouseman's Problem, Sokoban, and Rush Hour, I either strengthen existing results, or provide new, simpler hardness proofs than the original proofs.by Robert Aubrey Hearn.Ph.D

Hardness of Games and Graph Sampling

The work presented in this document is divided into two parts. The �rst part presents the hardness of games and the second part presents Graph sampling. Non-deterministic constraint logic[1] is used to prove the hardness of games. The games which are considered in this work is Reversi (2 player bounded game), Peg Solitaire (single player bounded game), Badland (single player bounded game). It also contains a theoretical study of peg solitaire on special graph classes. Reversi is proved to be PSPACE-Complete using Bounded 2CL, Peg Solitaire is proved to be NP-Complete using Bounded NCL. Badland is proved to be NP-Complete by a reduction from 3-SAT. The objective of study of peg solitaire of special graph classes is to �nd the maximum number of marbles we can remove from a fully �lled board, if the player is given the privilege to remove a marble from any cell initially, then following the rules after the initial move. The second part of the work is dedicated to graph sampling. Given a graph G, we try to sample a represen- tative subgraph Gs which is similar to the original graph G. The properties that are being studied are Degree Distribution, Clustering Coefficient, Average Shortest Path Length, Largest Connected Component Size. To measure the similarity between the original graph and sample we use the metrics Kolmogorov - Smirnov test and Kullback - Leibler divergence test. Tightly Induced Edge Sampling performs well on general graphs but it's performance decreases when the graph is a tree. Overall TIBFS and KARGER produces a sample which closely matches the distribution of original graphs.

Complexity of Unordered CNF Games

The classic TQBF problem is to determine who has a winning strategy in a game played on a given CNF formula, where the two players alternate turns picking truth values for the variables in a given order, and the winner is determined by whether the CNF gets satisfied. We study variants of this game in which the variables may be played in any order, and each turn consists of picking a remaining variable and a truth value for it. - For the version where the set of variables is partitioned into two halves and each player may only pick variables from his/her half, we prove that the problem is PSPACE-complete for 5-CNFs and in P for 2-CNFs. Previously, it was known to be PSPACE-complete for unbounded-width CNFs (Schaefer, STOC 1976). - For the general unordered version (where each variable can be picked by either player), we also prove that the problem is PSPACE-complete for 5-CNFs and in P for 2-CNFs. Previously, it was known to be PSPACE-complete for 6-CNFs (Ahlroth and Orponen, MFCS 2012) and PSPACE-complete for positive 11-CNFs (Schaefer, STOC 1976)