Resumen en Inglés:

Abstract Interpreted as a difficulty in determining relevance, the epistemological frame problem was a central source of debate within Cognitive Science during the 1980s and 1990s and has received renewed attention in recent discussions. Rather than assuming that the problem has been resolved, this paper argues that the frame problem remains a substantive challenge for contemporary Cognitive Science and Artificial Intelligence. In recent years, several alternatives to classical cognitivism emphasizing agent-environment interaction have revisited the problem of relevance determination. This paper examines whether such approaches provide sufficiently explicit accounts of relevance under dynamic conditions. While appeals to situated cognition help constrain inferential possibilities and reduce computational load, we argue that they do not dissolve the frame problem, since expectations, goals, and accumulated knowledge reintroduce an open-ended space of relevance. The main contribution of this work is to clarify why the frame problem persists even situated character of cognition, and to show that addressing it requires more than environmental or bodily constraints, pointing instead to the explanatory demands imposed by relevance determination in dynamic contexts.