11 citations · 13 across the 2 of their papers we have counts for
6 papers · 1 filter
Bridging Commonsense Reasoning and Probabilistic Planning via a Probabilistic Action Language
Yi Wang, Shiqi Zhang, Joohyung Lee
To be responsive to dynamically changing real-world environments, an intelligent agent needs to perform complex sequential decision-making tasks that are often guided by commonsens…
Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+
Yi Wang, Joohyung Lee
We extend probabilistic action language pBC+ with the notion of utility as in decision theory. The semantics of the extended pBC+ can be defined as a shorthand notation for a decis…
Weight Learning in a Probabilistic Extension of Answer Set Programs
Joohyung Lee, Yi Wang
LPMLN is a probabilistic extension of answer set programs with the weight scheme derived from that of Markov Logic. Previous work has shown how inference in LPMLN can be achieved.…
A Probabilistic Extension of Action Language BC+
Joohyung Lee, Yi Wang
We present a probabilistic extension of action language BC+. Just like BC+ is defined as a high-level notation of answer set programs for describing transition systems, the propose…
Computing LPMLN Using ASP and MLN Solvers
Joohyung Lee, Samidh Talsania, Yi Wang
LPMLN is a recent addition to probabilistic logic programming languages. Its main idea is to overcome the rigid nature of the stable model semantics by assigning a weight to each r…
On the Semantic Relationship between Probabilistic Soft Logic and Markov Logic
Joohyung Lee, Yi Wang
Markov Logic Networks (MLN) and Probabilistic Soft Logic (PSL) are widely applied formalisms in Statistical Relational Learning, an emerging area in Artificial Intelligence that is…