Reasoning about soft constraints and conditional preferences: complexity results and approximation techniques

Details Reasoning about soft constraints and conditional preferences: complexity results and approximation techniques Reasoning about soft constraints and conditional preferences: complexity results and approximation techniques

2009-05-22

arxiv.org/abs/0905.3766v1

IJCAI 2003: 215-220

Computer Science

Artificial Intelligence

Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-03)

Scientific paper

Many real life optimization problems contain both hard and soft constraints, as well as qualitative conditional preferences. However, there is no single formalism to specify all three kinds of information. We therefore propose a framework, based on both CP-nets and soft constraints, that handles both hard and soft constraints as well as conditional preferences efficiently and uniformly. We study the complexity of testing the consistency of preference statements, and show how soft constraints can faithfully approximate the semantics of conditional preference statements whilst improving the computational complexity

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