Releases: logic-and-learning-lab/Popper
Releases · logic-and-learning-lab/Popper
v4.3.0
v4.2.0
- filter programs we add to the combine stage
- only build variants using existing variables when the size is bound
- replace internal representation of example coverage from sets to bit arrays
v4.1.1
- Slightly improved constraints
- Fixed weird Clingo issue
v4.1.0
- Try to deduce BK constraints by default
- Improved testing via Janus
- WIP on improving the constrain stage (only working for single-rule programs)
v4.0.0
v3.1.0
- The ability to use different MaxSAT solvers
- Automatically try to detect Datalog BK
- Optimisation for the combine stage when learning programs from noiseless data
v3.0.0
Lots of changes, including:
- Support for learning optimal (MDL) programs from noisy data (https://arxiv.org/pdf/2308.09393.pdf) with the
--noisy
flag. - Use SAT and MaxSAT solvers to improve efficiency
v2.1.0
Major changes:
- Popper now finds minimal unsatisfiable cores of totally incomplete programs, as described in the paper: Learning Logic Programs by Finding Minimal Unsatisfiable Cores, A. Cropper and C. Hocquette, AAAI 2023, which should reduce learning times a lot
Minor changes:
- Faster way to test single rule programs
- Experimental feature to discover constraints from the BK before searching as described in the paper: Learning Logic Programs By Discovering Where Not to Search, A. Cropper and C. Hocquette, AAAI 2023. Enable this feature with the
--bkcons
flag
v2.0.0
A new version of Popper
- The main change is a more efficient way of learning programs with multiple rules, especially non-recursive programs as described Learning programs by combining programs, https://arxiv.org/abs/2206.01614 and which is related to the paper Learning logic programs through divide, constrain, and conquer. A. Cropper. AAAI 2022.
v1.1.0
Messed up the naming with the previous version. This version fixes it. Popper can now be installed with the command pip install popper-ilp