An important question in agent-based systems is how to execute some planned action in a random way. The answer for this question is fundamental to keep the user s interest in some product, not just because it makes the experience less repetitive but also because it makes the product more realistic. This kind of action execution can be mainly applied on simulators, serious and entertainment games based on agent models. Sometimes the randomness can be reached by just generating random numbers. However, when creating a more complex product, it is recommended to use some statistical or stochastic knowledge to not ruin the product s consumption experience. In this work we try to give support to the creation of dynamic and interactive animation and story using an arbitrary model based on agents. Inspired on stochastic methods, we propose a new framework called D-Engine, which is able to create a random, but with a well-known expected behavior, set of timestamps describing the execution of an action in a discrete way following some specific rate. While these timestamps allow us to animate a story, an action or a scene, the mathematical results generated with our framework can be used to aid other applications such as result forecasting, nondeterministic planning, interactive media and storytelling. In this work we also present how to implement two different applications using our framework: a duel scenario and an interactive online auction website.