Dataset : Software
ETR Case Generator
- Documentation:
- The problem generation process is based on a randomized depth-first search for a list of View objects which will form the premises of a problem. The search incrementally chooses a random View object to append to the list, by means of randomly applying mutations to a random 'seed problem' and filtering for Views which keep the ETR-derived conclusion of the problem non-trivial. New View objects are incrementally added until the sum of the atom counts across the list is equal to one of a specified set of counts, representing a desired degree of complexity. If the greatest permitted atom count is exceeded, the last few View objects are backtracked. After too many failed attempts, the entire list is discarded and we start from scratch.
Actions
Access Document
- Files:
-
-
(Preview, Not applicable (or unknown), pdf, 74.9KB, Terms of use)
-
- Publication website:
- https://github.com/Oxford-HAI-Lab/etr_case_generator
Authors/Creators
Contributors
+ Koralus, P
- Institution:
- University of Oxford
- Division:
- HUMS
- Department:
- Philosophy
- Role:
- Contributor
- ORCID:
- 0000-0002-7271-1448
+ Wang-Mascianica, V
- Role:
- Contributor
+ Desai, J
- Role:
- Contributor
- Publisher:
- University of Oxford
- Publication date:
- 2025
- Language:
-
English
- Subtype:
-
Software
- Pubs id:
-
2350477
- UUID:
-
uuid_33edadc1-4c1d-4e2b-b1a4-717b8243c8a4
- Local pid:
-
pubs:2350477
- Deposit date:
-
2025-12-16
- ARK identifier:
Terms of use
- Copyright date:
- 2025
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