Frame Problem
The challenge of representing what does NOT change when an action is performed, without explicitly listing every unchanged fact.
Also known as: Frame Problem
Category: AI
Tags: ai, philosophies, logic, cognitive-science
Explanation
The frame problem, identified by McCarthy and Hayes in 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, philosophers like Hubert Dreyfus 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 purely computational theories of mind.
The problem manifests in three aspects: logical (how to represent non-change efficiently), computational (avoiding combinatorial explosion), and philosophical (how do minds determine relevance?). Modern AI addresses it through heuristics, neural networks, and learned representations rather than explicit logical enumeration.
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