 While rationality-over-time may have import in assessing an agent’s preferences and norms for changing these preferences (one can read the discussion in  Section 6.2  below in this way), there remains the important question of how an agent should act in light of her preferences at any given point in time. To this end, the sequential decision model can be fruitfully viewed as a tool for helping determine rational choice at a particular time, just like the static decision model. The sequential decision tree is effectively a way of visualising the temporal series of choices and learning events that an agent believes she will confront in the future, depending on what part of the decision tree she will find herself. The key question, then, is: How should an agent choose amongst her initial options in light of her projected decision tree? This question has generated a surprising amount of controversy. Three major approaches to negotiating sequential decision trees have appeared in the literature. These are the naïve or myopic approach, the sophisticated approach and the resolute approach. These will be discussed in turn; it will be suggested that the disputes may not be substantial but rather indicate subtle differences in the interpretation of sequential decision models.