Answer Set Programming for Judgment Aggregation

Authors: Ronald de Haan, Marija Slavkovik

IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We take advantage of this and propose a natural and modular encoding of various judgment aggregation procedures and related problems in JA into ASP. With these encodings, we achieve two results: (1) paving the way towards constructing a wide range of new benchmark instances (from JA) for answer set solving algorithms; and (2) providing an automated tool for researchers in the area of judgment aggregation.
Researcher Affiliation Academia Ronald de Haan1 and Marija Slavkovik2 1Institute for Logic, Language and Computation (ILLC), University of Amsterdam 2University of Bergen
Pseudocode Yes 1 agent(A) :voter(A). 2 lit(X;-X) :issue(X). 3 1 { js(A,X) ; js(A,-X) } 1 :agent(A), issue(X). 4 :agent(A), clause(C,_), js(A,-L) : clause(C,L).
Open Source Code Yes All encodings presented in this paper are available as online supplementary material: https://github.com/rdehaan/ja-asp.
Open Datasets No The paper mentions generating benchmarks from real-world data like the Pref Lib data set (footnote 1: http://www.preflib.org/data) for future use, but it does not report on experiments conducted within this paper that use this dataset for training.
Dataset Splits No The paper does not report on experimental results, therefore it does not provide details on training, validation, or test dataset splits.
Hardware Specification No The paper does not report on experimental results, and thus does not specify any hardware used.
Software Dependencies Yes The variant of the language that we use is that used by the Potsdam Answer Set Solving Collection [Gebser et al., 2011b; Gebser et al., 2017]. This language is a superset of the ASP-Core-2.0 standard [Calimeri et al., 2013]. Potassco user guide (v2.1.0).
Experiment Setup No The paper does not report on experimental results, and thus does not provide details on experimental setup or hyperparameters.