Enhancing Lazy Grounding with Lazy Normalization in Answer-Set Programming


  • Jori Bomanson Aalto University
  • Tomi Janhunen Aalto University
  • Antonius Weinzierl Vienna University of Technology




Answer-Set Programming (ASP) is an expressive rule-based knowledge-representation formalism. Lazy grounding is a solving technique that avoids the well-known grounding bottleneck of traditional ASP evaluation but is restricted to normal rules, severely limiting its expressive power. In this work, we introduce a framework to handle aggregates by normalizing them on demand during lazy grounding, hence relieving the restrictions of lazy grounding significantly. We term our approach as lazy normalization and demonstrate its feasibility for different types of aggregates. Asymptotic behavior is analyzed and correctness of the presented lazy normalizations is shown. Benchmark results indicate that lazy normalization can bring up-to exponential gains in space and time as well as enable ASP to be used in new application areas.




How to Cite

Bomanson, J., Janhunen, T., & Weinzierl, A. (2019). Enhancing Lazy Grounding with Lazy Normalization in Answer-Set Programming. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 2694-2702. https://doi.org/10.1609/aaai.v33i01.33012694



AAAI Technical Track: Knowledge Representation and Reasoning