本論文主要是在agent-based計算經濟體系下，利用Holland(1975)所提的遺傳演算法(genetic algorithms)作為計算工具，分別探討連鎖店賽局及寡占市場廠商價格策略的生態演化。

在連鎖店賽局的研究中，藉由agent-based計算經濟分析掠奪性定價的特性，並進一步探討參賽者價格策略的共演化(co-evolutionary)特性，及多元均衡賽局中均衡移轉的動態過程。針對賽局中不同的不確定性進行模擬，結果顯示廠商長期總合行為是否穩定，和賽局中的不確定程度有相當的關聯。另外，弱獨占者和潛在競爭者的價格策略存在著共演化特性。在此演化賽局中，Nash均衡雖非穩定均衡解，但卻最常浮現在長期總合行為中。因此，Nsah均衡對agent-based演化賽局的結果而言，相當具有參考價值。在特定的不確定程度下，長期總合行為似乎只在某些特定的Nash均衡中徘徊。這些移轉途徑並不具有對稱性，甚至移轉速度也非對稱。本研究所呈現的演化結果跳脫一般對均衡的觀念，展現出傳統理論所無法預知的共演化特性，並呈現出非對稱的吸引環。

此外，同樣在Agent-based計算經濟下探討寡占市場廠商策略生態。本研究首先闡明N參賽者囚犯兩難重複賽局和N廠商寡占賽局之間的異同，經由寡占賽局廠商償付矩陣(payoff matrix)的狀態相依馬可夫移轉矩陣( state-dependent Markov transition matrix)性質，說明N廠商寡占賽局和N參賽者囚犯兩難重複賽局的差異。其次，透過三家廠商寡占賽局的模擬實驗，以遺傳演算法建構參賽廠商的適應性行為，分別以寡占市場生態上的表現型(phenotypes)和基因型(genotype)進行分析。20次模擬結果所呈現的最終市場狀態相當分歧，有形成吸引環的三廠商寡占市場、有收斂到價格戰的三廠商寡占市場。另外也成功的模擬出三廠商寡占市場演化至雙佔市場、甚或獨占市場的過程。但是，在眾多模擬中並沒有發現持續的勾結定價狀態，反而掠奪性價格是較主要的價格策略。這些結果相對於實際經濟社會中的寡占市場，給予一個活潑生動的範例。

Recently, genetic algorithms have been extensively applied to modeling evolution game in agent-based computational economic.　While these applications advance our understanding of evolution game, they have generated some new phenomena that have not been well treated in conventional game theory.

In the first topic, we shall systemize the study of one of these new phenomena, namely, coevolutionary instability. We exemplify the basic properties of coevolutionary instability by the chain store game, which is the game frequently used to study the role of reputation effects in economics.　In addition, we point out that, while, due to uncertainty effects, Nash equilibria can no longer be stable, and they can still help us predict the dynamic process of the game.　In particular, we can see that the dynamic process of the game is well captured by a few Nash equilibria and the transition among them.　A careful study can uncover several interesting patterns and we show the impact of uncertainty on these patterns.

In the second topic, the relation between the N-person IPD game and the N-person oligopoly game is rigorously addressed.　Our analytical framework shows that due to the path-dependence of the payoff matrix of the oligopoly game, the two games in general are not close in spirit.　We then further explore the significance of the path-dependence property to the rich ecology of oligopoly from an evolutionary perspective.　More precisely, we simulated the evolution of a 3-person oligopoly game, and showed that the rich ecology of oligopoly can be exhibited by modeling the adaptive behavior of oligopolists with genetic algorithms.　The emergent behavior of oligopolists are presented and analyzed.　We indicate how the path-dependence nature may shed light on the phenotypes and genotypes coming into existence.