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The Centre for Computational Law has merged with the Centre for AI and Data Governance to form the Centre for Digital Law. The new Centre examines the transformative impact of digital technologies on legal systems, government, society, and economy. Our research, including the Research Programme on Computational Law, continue under its ambit. Our current website will remain operational in this transitional period but we strongly encourage you to visit our new website at cdl.smu.edu.sg and explore the updated features and content. If you have any questions or need assistance, please contact our support team at cclawadmin@smu.edu.sg.

User Guided Abductive Proof Generation for Answer Set Programming Queries

We present a method for generating possible proofs of a query with respect to a given Answer Set Programming (ASP) rule set using an abductive process where the space of abducibles is automatically constructed just from the input rules alone. Given a (possibly empty) set of user provided facts, our method infers any additional facts that may be needed for the entailment of a query and then outputs these extra facts, without the user needing to explicitly specify the space of all abducibles. We also present a method to generate a set of directed edges corresponding to the justification graph for the query. Furthermore, through different forms of implicit term substitution, our method can take user provided facts into account and suitably modify the abductive solutions. Past work on abduction has been primarily based on goal directed methods. However these methods can result in solvers that are not truly declarative. Much less work has been done on realizing abduction in a bottom up solver like the Clingo ASP solver. We describe novel ASP programs which can be run directly in Clingo to yield the abductive solutions and directed edge sets without needing to modify the underlying solving engine.

Associated People

Principal Research Scientist
Martin Strecker
Principal Investigator
Wong Meng Weng