class HerdBehavior:
    """
    In economics, the herd effect or "herd behavior" refers to the tendency of individuals to follow the actions and behaviors of a larger group, even if it goes against their own independent judgment or rational decision-making. The characteristics of herd behavior in economics include:

    Informational cascade: The herd effect is often driven by an informational cascade, in which individuals make decisions based on the actions of others, rather than on their own independent research or analysis.
    Emotional contagion: Herd behavior is also often driven by emotional contagion, where individuals are influenced by the emotions and feelings of others, rather than by their own independent thoughts or feelings.
    Mimicry: Herd behavior is characterized by individuals who mimic the actions and behaviors of others, rather than making independent decisions based on their own analysis.
    Irrational decision-making: The herd effect often leads to irrational decision-making, as individuals follow the actions of the group, rather than making decisions based on their own analysis or rational thought.
    Amplification of risk: Herd behavior can also amplify the risks and uncertainties in the market, as the actions of the group can lead to a self-fulfilling prophecy, where the initial action becomes a catalyst for further action by the group.
    Overall, the herd effect in economics is a phenomenon in which individuals are influenced by the actions and behaviors of a larger group, even if it goes against their own rational judgment or independent decision-making. This can lead to irrational decision-making, amplified risks, and a lack of independent analysis and research.
    这个类实现了一个简单的机制，模拟了信息传递和决策过程。每个实例维护一个决策列表，每次决策时，它将当前的决策添加到列表中，并检查前一个决策是否与当前的决策相同。如果前一个决策与当前决策相同，则返回当前决策；否则，返回前一个决策，模拟了羊群效应中的“模仿”特征。

    为了实现羊群效应的其他特征，我们需要在类中添加其他方法。例如，我们可以实现 emotional_contagion 方法来模拟情感传染，或实现 amplify_risk 方法来模拟风险放大。
    """
    def __init__(self):
        self.decisions = []
    
    def make_decision(self, decision):
        self.decisions.append(decision)
        if len(self.decisions) > 1:
            last_decision = self.decisions[-2]
            if last_decision == decision:
                return decision
            else:
                return last_decision
        else:
            return decision
    
    def emotional_contagion(self, emotion):
        # This method is a placeholder for implementing emotional contagion
        pass
    
    def mimicry(self, behavior):
        # This method is a placeholder for implementing mimicry
        pass
    
    def amplify_risk(self, risk):
        # This method is a placeholder for implementing risk amplification
        pass
