Goals are used to define the behavior of (pro-active) agents. It is our view that the goals of an agent can be seen as a knowledge base of the situations that it wants to achieve. It is therefore in a natural way that we use Dynamic Logic Programming (DLP), an extension of AnswerSet Programming that allows for the representation of knowledge that changes with time, to represent the goals of the agent and their evolution, in a simple, declarative, fashion. In this paper, we represent agent's goals as a DLP, discuss and show how to represent some situations where the agent should adopt or drop goals, and investigate some properties that emerge from using such representation.