Abstract
We consider voting over combinatorial domains, where alternatives are binary tuples. We assume that votes are specified as conditionally lexicographic preference trees, or LP trees for short. We study the aggregation of LP tree votes for several positional scoring rules. Our main goal is to demonstrate that answer-set programming tools can be effective in solving the winner and the evaluation problems for instances of practical sizes. To this end, we propose encodings of the two problems as answer-set programs, design methods to generate LP tree votes randomly to support experiments, and present experimental results obtained with ASP solvers clingo and clingcon.
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Liu, X., Truszczynski, M. (2013). Aggregating Conditionally Lexicographic Preferences Using Answer Set Programming Solvers. In: Perny, P., Pirlot, M., Tsoukiàs, A. (eds) Algorithmic Decision Theory. ADT 2013. Lecture Notes in Computer Science(), vol 8176. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41575-3_19
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DOI: https://doi.org/10.1007/978-3-642-41575-3_19
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