标题： 一种细胞自动机方法用于捐赠博弈 显示英文标题

标题： A Cellular Automata Approach to Donation Game

摘要： 捐赠游戏是研究多智能体系统中合作的出现和进化的一个成熟框架。 合作行为可能受到部分可观测环境中环境噪声的影响，以及智能体决策策略的影响，这些策略可能不仅包括声誉，还包括慷慨和宽恕等特质。 传统的模拟通常假设完全随机的互动，其中合作是在随机选择的智能体对之间进行测试的。 在本文中，我们使用斯蒂芬·沃尔夫勒姆的一维二进制细胞自动机的概念来研究合作动力学。 这种方法使我们能够探索当互动仅限于相邻智能体时，合作如何演化。 我们定义了符合捐赠游戏机制的二进制细胞自动机规则。 此外，我们引入了感知和行动噪声模型，以及一个控制智能体策略概率演化的变异矩阵。 我们的实证结果表明，合作显著受到智能体移动性和他们在游戏板上的空间局部性的影响。 这些发现突显了区分完全随机的多智能体系统与那些智能体更可能与其最近邻居互动的系统的重要性。 显示英文摘要

摘要： The donation game is a well-established framework for studying the emergence and evolution of cooperation in multi-agent systems. The cooperative behavior can be influenced by the environmental noise in partially observable settings and by the decision-making strategies of agents, which may incorporate not only reputation but also traits such as generosity and forgiveness. Traditional simulations often assume fully random interactions, where cooperation is tested between randomly selected agent pairs. In this paper, we investigate cooperation dynamics using the concept of Stephen Wolfram's one-dimensional binary cellular automata. This approach allows us to explore how cooperation evolves when interactions are limited to neighboring agents. We define binary cellular automata rules that conform to the donation game mechanics. Additionally, we introduce models of perceptual and action noise, along with a mutation matrix governing the probabilistic evolution of agent strategies. Our empirical results demonstrate that cooperation is significantly affected by agents' mobility and their spatial locality on the game board. These findings highlight the importance of distinguishing between entirely random multi-agent systems and those in which agents are more likely to interact with their nearest neighbors.