Interacting Answer Sets

Author(s):  
Chiaki Sakama ◽  
Tran Cao Son
Keyword(s):  
Author(s):  
Zeynep G. Saribatur ◽  
Thomas Eiter

The recently introduced notion of ASP abstraction is on reducing the vocabulary of a program while ensuring over-approximation of its answer sets, with a focus on having a syntactic operator that constructs an abstract program. It has been shown that such a notion has the potential for program analysis at the abstract level by getting rid of irrelevant details to problem solving while preserving the structure, that aids in the explanation of the solutions. We take here a further look on ASP abstraction, focusing on abstraction by omission with the aim to obtain a better understanding of the notion. We distinguish the key conditions for omission abstraction which sheds light on the differences to the well-studied notion of forgetting. We demonstrate how omission abstraction fits into the overall spectrum, by also investigating its behavior in the semantics of a program in the framework of HT logic.


Author(s):  
Giovanni Amendola ◽  
Thomas Eiter ◽  
Nicola Leone
Keyword(s):  

AI Magazine ◽  
2016 ◽  
Vol 37 (3) ◽  
pp. 25-32 ◽  
Author(s):  
Benjamin Kaufmann ◽  
Nicola Leone ◽  
Simona Perri ◽  
Torsten Schaub

Answer set programming is a declarative problem solving paradigm that rests upon a workflow involving modeling, grounding, and solving. While the former is described by Gebser and Schaub (2016), we focus here on key issues in grounding, or how to systematically replace object variables by ground terms in a effective way, and solving, or how to compute the answer sets of a propositional logic program obtained by grounding.


Author(s):  
Sergei Odintsov ◽  
David Pearce
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Author(s):  
Steven Schockaert ◽  
Jeroen Janssen ◽  
Dirk Vermeir ◽  
Martine De Cock
Keyword(s):  

Author(s):  
Albert Kalim ◽  
Jane Huffman Hayes ◽  
Satrio Husodo ◽  
Erin Combs ◽  
Jared Payne
Keyword(s):  

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