TY - JOUR
T1 - The joy of Probabilistic Answer Set Programming
T2 - Semantics, complexity, expressivity, inference
AU - Cozman, Fabio Gagliardi
AU - Mauá, Denis Deratani
N1 - Publisher Copyright:
© 2020 Elsevier Inc.
PY - 2020/10
Y1 - 2020/10
N2 - Probabilistic Answer Set Programming (PASP) combines rules, facts, and independent probabilistic facts. We argue that a very useful modeling paradigm is obtained by adopting a particular semantics for PASP, where one associates a credal set with each consistent program. We examine the basic properties of PASP under this credal semantics, in particular presenting novel results on its complexity and its expressivity, and we introduce an inference algorithm to compute (upper) probabilities given a program.
AB - Probabilistic Answer Set Programming (PASP) combines rules, facts, and independent probabilistic facts. We argue that a very useful modeling paradigm is obtained by adopting a particular semantics for PASP, where one associates a credal set with each consistent program. We examine the basic properties of PASP under this credal semantics, in particular presenting novel results on its complexity and its expressivity, and we introduce an inference algorithm to compute (upper) probabilities given a program.
KW - Answer Set Programming
KW - Computational complexity
KW - Credal sets
KW - Descriptive complexity
KW - Logic programming
KW - Probabilistic programming
UR - http://www.scopus.com/inward/record.url?scp=85089471558&partnerID=8YFLogxK
U2 - 10.1016/j.ijar.2020.07.004
DO - 10.1016/j.ijar.2020.07.004
M3 - Artículo
AN - SCOPUS:85089471558
SN - 0888-613X
VL - 125
SP - 218
EP - 239
JO - International Journal of Approximate Reasoning
JF - International Journal of Approximate Reasoning
ER -