In this paper we present a model for defeasible decision making that combines decision rules and arguments. In this decision framework we can change the agent's decision policy in a flexible way, with minor changes in the criteria that influence the agent's preferences and the comparison of arguments. Our approach includes a simple methodology for developing the decision components of the agent. A decision framework designed with this methodology exhibits some interesting properties. If the agent (decision maker) has available all the relevant knowledge about its preferences among the different alternatives that could be conceivably posed to it, then our proposal implements a rational preference relation. In opposition, if the agent has partial knowledge about its preferences, the decisions made by the agent still exhibits a behavior consistent with the weak axiom of revealed preference of the choice-based approach, a more flexible approach to Individual Decision Making than the preference-based approach. The principles stated in this work are exemplified in a robotic domain, where a robot should make decisions about which box must be transported next.