no code implementations • 6 Jun 2023 • Michael Gelfond, Jorge Fandinno, Evgenii Balai
This paper presents a rich knowledge representation language aimed at formalizing causal knowledge.
no code implementations • 17 Aug 2021 • Jorge Fandinno, Wolfgang Faber, Michael Gelfond
The language of epistemic specifications and epistemic logic programs extends disjunctive logic programs under the stable model semantics with modal constructs called subjective literals.
no code implementations • 21 Aug 2018 • Michael Gelfond, Yuanlin Zhang
The paper presents a knowledge representation language $\mathcal{A}log$ which extends ASP with aggregates.
no code implementations • 29 Aug 2016 • Michael Gelfond, Yuanlin Zhang
The paper continues the investigation of Poincare and Russel's Vicious Circle Principle (VCP) in the context of the design of logic programming languages with sets.
no code implementations • 17 Aug 2015 • Mohan Sridharan, Michael Gelfond, Shiqi Zhang, Jeremy Wyatt
This paper describes an architecture for robots that combines the complementary strengths of probabilistic graphical models and declarative programming to represent and reason with logic-based and probabilistic descriptions of uncertainty and domain knowledge.
no code implementations • 19 May 2015 • Daniela Inclezan, Michael Gelfond
It is based on the approach of Gelfond and Lifschitz (1993; 1998) in which a high-level action language is used as a front end for a logic programming system description.
no code implementations • 14 May 2014 • Michael Gelfond, Yuanlin Zhang
The paper presents a knowledge representation language $\mathcal{A}log$ which extends ASP with aggregates.
no code implementations • 5 May 2014 • Shiqi Zhang, Mohan Sridharan, Michael Gelfond, Jeremy Wyatt
This paper describes an architecture that combines the complementary strengths of declarative programming and probabilistic graphical models to enable robots to represent, reason with, and learn from, qualitative and quantitative descriptions of uncertainty and knowledge.