Programming with Propositional Schemata: An Implementation and Its Implications

Title: Programming with Propositional Schemata: An Implementation and Its Implications

Research Question: How can propositional schemata be used to enhance the efficiency and effectiveness of answer-set programming?

Methodology: The researchers developed an implementation of answer-set programming called aspps, which stands for answer-set programming with propositional schemata. This system processes PS+-theories, which are based on the extended logic of propositional schemata with a closed world assumption. The system consists of two main parts: psgrnd, which grounds the PS+-theory, and aspps, which is the solver that computes models of grounded PS+-theories.

Results: The researchers found that aspps can process PS+-theories more efficiently than existing systems like smodels and dlv. This is due to the use of propositional schemata, which allow for better representation and handling of cardinality constraints on sets. The system aspps was able to compute models of grounded PS+-theories effectively, demonstrating its potential for solving complex problems.

Implications: The implementation of aspps has several implications for the field of answer-set programming. First, it provides a new approach to answer-set programming that can lead to more efficient and effective solutions. Second, it demonstrates the potential of propositional schemata as a tool for enhancing the capabilities of answer-set programming systems. Finally, the research highlights the importance of grounding in the context of answer-set programming, as it plays a crucial role in the performance of the system.

Link to Article: https://arxiv.org/abs/0107029v1 Authors: arXiv ID: 0107029v1