# Frame Problem The frame problem, identified by McCarthy and Hayes (1969), asks how an AI system can efficiently determine what *doesn't* change when an action is taken. If a robot moves a box, the box's location changes—but millions of other facts (the color of the walls, the time of day, gravity) remain the same. How does the system avoid re-checking everything? Originally a technical AI problem, [[Hubert Dreyfus]] and others argued it reveals a deeper issue: classical AI struggles with relevance—knowing what matters in a situation. Humans effortlessly filter irrelevant information; symbol-manipulating systems cannot. The frame problem became a key argument for [[Embodied Cognition]] and against [[Computational Theory of Mind]]. Modern AI addresses it through heuristics, neural networks, and learned representations. ## The Problem | Aspect | Challenge | |--------|-----------| | Logical | How to represent non-change efficiently | | Computational | Avoiding combinatorial explosion | | Philosophical | How do minds determine relevance? | ## References - McCarthy & Hayes. "Some Philosophical Problems from the Standpoint of AI" (1969) - Dennett, Daniel. "Cognitive Wheels: The Frame Problem of AI" (1984) ## Related - [[Hubert Dreyfus]] - [[Artificial Intelligence (AI)]] - [[Computational Theory of Mind]] - [[Symbol Grounding Problem]]