"Egyptian Ratscrew" (ERS) is a modern American card game enjoyed by millions of players worldwide. A game of ERS is won by collecting all of the cards in the deck. Typically this game is won by the player with the fastest reflexes, since the most common strategy for collecting cards is being the first to slap the pile in the center whenever legal combinations of cards are placed down. Most players assume that the dominant strategy is to develop a faster reaction time than your opponents, and no academic inquiry has been levied against this assumption. This thesis investigates the hypothesis that a "risk slapping" strategist who relies on practical economic decision making will win an overwhelming majority of games against players who rely on quick reflexes alone. It is theorized that this can be done by exploiting the "burn rule," a penalty that is too low-cost to effectively dissuade players from slapping illegally when it benefits them. Using the Ruby programming language, we construct an Egyptian Ratscrew simulator from scratch. Our model allows us to simulate the behavior of 8 strategically unique players within easily adjustable parameters including simulation type, player count, and burn amount. We simulate 100k iterations of 67 different ERS games, totaling 6.7 million games of ERS, and use win percentage data in order to determine which strategies are dominant under each set of parameters. We then confirm our hypothesis that risk slapping is a dominant strategy, discover that there is no strictly dominant approach to risk slapping, and elucidate a deeper understanding of different ERS mechanics such as the burn rule. Finally, we assess the implications of our findings and suggest potential improvements to the rules of the game. We also touch on the real-world applications of our research and make recommendations for the future of Egyptian Ratscrew modeling.

翻译："埃及老鼠接龙"(ERS)是一种深受全球数百万玩家喜爱的现代美式纸牌游戏。该游戏的获胜方式为收集牌堆中的所有卡牌。通常，反应最快的玩家更容易获胜，因为收集卡牌最常见的策略就是在台面出现合法牌型组合时率先拍击中央牌堆。多数玩家认为主导策略是培养比对手更快的反应速度，而这一假设从未受到学术质疑。本文研究假设：采用"风险拍击"策略、基于实用经济决策的玩家，将在与仅依赖快速反应的玩家的对局中赢得压倒性多数。理论认为，这可通过利用"烧牌规则"实现——该惩罚机制成本过低，无法有效阻止玩家在获益时进行违规拍击。我们使用Ruby编程语言从零构建了埃及老鼠接龙模拟器。该模型可在可调参数（包括模拟类型、玩家数量和烧牌数量）下模拟8种策略差异型玩家的行为。我们通过模拟67种不同ERS游戏的10万次迭代（总计670万局ERS对局），利用胜率数据确定各参数设定下的主导策略。最终验证了"风险拍击为主导策略"的假设，发现不存在严格占优的风险拍击方式，并深化了对烧牌规则等ERS机制的理解。最后，我们评估研究启示并提出游戏规则改进建议，同时探讨研究成果的现实应用场景，为未来ERS建模提出方向性建议。