His primary scientific interests are in Artificial intelligence, Logic programming, Programming language, Theoretical computer science and Non-monotonic logic. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning, Semantics and Calculus. His work carried out in the field of Logic programming brings together such families of science as Autoepistemic logic and Knowledge representation and reasoning.
His study in Theoretical computer science focuses on Predicate logic in particular. His research in Stable model semantics intersects with topics in Well-founded semantics and Axiomatic semantics. His studies deal with areas such as Multimodal logic, Description logic, Higher-order logic, Logical programming and Semantics as well as Well-founded semantics.
Marc Denecker mainly focuses on Theoretical computer science, Logic programming, Programming language, Knowledge representation and reasoning and Artificial intelligence. He works mostly in the field of Theoretical computer science, limiting it down to topics relating to Inference and, in certain cases, Knowledge base, as a part of the same area of interest. His Logic programming research includes themes of Autoepistemic logic, Semantics, Classical logic and Description logic.
The Autoepistemic logic study combines topics in areas such as Non-monotonic logic and Higher-order logic. His work deals with themes such as Algorithm and Extension, which intersect with Knowledge representation and reasoning. His Artificial intelligence research incorporates elements of Machine learning, Representation and Natural language processing.
The scientist’s investigation covers issues in Semantics, Programming language, Theoretical computer science, Logic programming and Knowledge representation and reasoning. The various areas that he examines in his Programming language study include Basis and Principle of compositionality. His Theoretical computer science research incorporates themes from Context, Human–computer interaction, Knowledge base, Graph and Solver.
Marc Denecker interconnects Domain, Fixed point, Formal language, Type and Autoepistemic logic in the investigation of issues within Logic programming. His work in Autoepistemic logic addresses issues such as Well-founded semantics, which are connected to fields such as Calculus. His Knowledge representation and reasoning study is concerned with the field of Artificial intelligence as a whole.
His scientific interests lie mostly in Knowledge representation and reasoning, Programming language, Logic programming, Modeling language and Theoretical computer science. His Knowledge representation and reasoning research incorporates elements of Mathematical logic, Declarative programming and Calculus. The Programming language study combines topics in areas such as Basis, Algorithm and TRACE.
His Logic programming study contributes to a more complete understanding of Artificial intelligence. His studies in Artificial intelligence integrate themes in fields like Well-founded semantics and Argumentation theory. He studies Answer set programming, a branch of Theoretical computer science.
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Abduction in Logic Programming
Marc Denecker;Antonis C. Kakas.
Lecture Notes in Computer Science (2002)
Well-founded and stable semantics of logic programs with aggregates
Nikolay Pelov;Marc Denecker;Maurice Bruynooghe.
Theory and Practice of Logic Programming (2007)
A logic of nonmonotone inductive definitions
Marc Denecker;Eugenia Ternovska.
ACM Transactions on Computational Logic (2008)
The Second Answer Set Programming Competition
Marc Denecker;Joost Vennekens;Stephen Bond;Martin Gebser.
international conference on logic programming (2009)
Approximations, stable operators, well-founded fixpoints and applications in nonmonotonic reasoning
Marc Denecker;Victor Marek;Miroslaw Truszczyński.
Logic-based artificial intelligence (2000)
Cp-logic: A language of causal probabilistic events and its relation to logic programming
Joost Vennekens;Marc Denecker;Maurice Bruynooghe.
Theory and Practice of Logic Programming (2009)
SLDNFA: An abductive procedure for abductive logic programs
Marc Denecker;Danny de Schreye.
Journal of Logic Programming (1998)
Representing incomplete knowledge in abductive logic programming
Marc Denecker;Danny de Schreye.
Journal of Logic and Computation (1995)
SLDNFA: an abductive procedure for normal abductive programs
Marc Denecker;Danny De Schreye.
Proc. of the International Joint Conference and Symposium on Logic Programming (1992)
Extending Classical Logic with Inductive Definitions
Lecture Notes in Computer Science (2000)
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