The Frame Problem
Updated 2026-09-10
INTRODUCTION
English translation pending.
CORE DEFINITION
For most artificial intelligence researchers, the frame problem is how to represent the consequences of actions in logic without explicitly representing the large number of intuitively obvious non-consequences. For many philosophers, it also suggests a broader epistemological problem about how a system can limit inference to what is relevant without surveying everything it knows.
SCAFFOLDING EFFECT
Reduce cognitive load
- Compress inference: represent explicitly only the part of the state that the action changes and let the rest stay by default. - Identify relevance: ask which facts genuinely need to be included, avoiding computation spent on irrelevant detail. - Justify the default: state why the inertia assumption is safe here and check what would break it.
Anchor fast decisions
A single action changes only a small part of the world, while the rest stays largely as it was. Without such an inertia assumption, a formal system must assert explicitly, item by item, which things did not change, and the size of the inference explodes; the crux is therefore how to build relevance constraints into the representation itself.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- plato.stanford.eduhttps://plato.stanford.edu/entries/frame-problem/verified
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