Exact sampler for UFO2 with tree and cardinality constraints. This tool is for randomly generation of instances or combinatorical structures from extended UFO2 theory.
- Markov Logic Network (MLN) format, also see Pracmln
- Tree constraint:
Tree[R] - Cardinality constraint:
|P| = k
A friends-smokes MLN:
person = {C1, C2, C3, C4, C5, C6}
friends(person,person)
smokes(person)
3 smokes(x)
// NOTE: only support CNF for now
1 !friends(x,y) v !smokes(x) v smokes(y) # i.e., friends(x,y) ^ smokes(x) => smokes(y).
2 colored tree:
vertex = 9
E(vertex, vertex)
red(vertex)
black(vertex)
!E(x,x).
!E(x,y) v E(y,x).
red(x) v black(x).
!red(x) v !black(x).
(!E(x,y) v !red(x) v !red(y)) ^ (!E(x,y) v !black(x) v !black(y)).
Tree[E]
2 red-black tree with exact k red vertices:
vertex = 9
E(vertex, vertex)
red(vertex)
black(vertex)
!E(x,x).
!E(x,y) v E(y,x).
red(x) v black(x).
!red(x) v !black(x).
(!E(x,y) v !red(x) v !red(y)) ^ (!E(x,y) v !black(x) v !black(y)).
Tree[E]
|a| = 4
More examples are in models
Install requirements:
$ pip install -r requirements.txt
Add path to your PYTHONPATH:
$ export PYTHONPATH=$(pwd)/sampling_ufo2:$PYTHONPATH
Run the following command:
$ python sampling_ufo2/sampler.py -i models/friendsmoker.mln -k 10
Find more arguments:
$ python sampling_ufo2/sampler.py -h
Yuanhong Wang, Timothy van Bremen, Yuyi Wang and Ondřej Kuželka. Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions. AAAI 2022
Compared with the original algorithm in the paper, this repo implements a faster version, incorporating efficient caching, see algorithm discription for details.