本研究以Chen-Chie（Chen and Chie, 2007）所設計的代理人基模型，探討所得分配對彩券銷售額的影響。這篇論文考量了兩種彩券參與函數，一種是採用模糊推論的方法來呈現代理人購買彩券的決定，在此方式下，並未將可能中奬的期望效果納入。另一種則是以預期效用理論為主軸，並且加入主觀認知的中獎機率。除了彩券參與度外，根據Chen and Chie (2007)的設計，還考慮到兩個購買彩券經驗的觀點，分別是自我意識選號及個體間的獨立性。模型中代理人參數並未固定，取而代之的，是讓代理人具有自動產生參數的能力，所有行為的參數是以遺傳演算法取得其適應性。當代理人進行遺傳演算（社會學習）時，代理人對策略的學習會依照區間的設定，進一步作區域性社會學習及全域社會學習。本論文彙集了上述設計，提供了四種彩券市場行為模型，配合不同的所得分配進行模擬，並且利用統計檢定比較其統計量的變化，分析所得分配對彩券銷售額的影響。 / This study addresses the impact of income distribution on lottery sales using an agent-based modeling approach, specifically, the Chen-Chie model (Chen and Chie, 2007). Two kinds of lottery participation function are considered in this thesis. One is more heuristic and does not require agents’ expectations of the odds. In this case, we use the fuzzy inference system to represent agents’ heuristics. The other explicitly takes agents’ expectations of the odds into account, and a formal expected utility maximization approach is taken. In addition to lottery participation, following Chen and Chie (2007), we also consider two additional empirical aspects of lottery plays, namely, conscious selection and state-dependent utilities. The parameters of agents are not fixed; instead, they are autonomous and all behavioral parameters are adaptive via genetic algorithms. While the population genetic algorithms (social learning) are applied, an idea of nearest neighbors learning is used to further distinguish the global social learning from the local social learning. These setups together give us four behavioral models of lottery markets. We then simulate each of these four markets with different income distribution, and then compare their statistic behavior with statistical test to examine the overall effect of income distribution to lottery sales.