Automata Techniques for Temporal Answer Set Programming
This work addresses dynamic reasoning challenges in AI and logic programming, but it appears incremental as it builds on existing temporal ASP extensions.
The research tackles dynamic problems in Answer Set Programming by proposing to integrate automata-based techniques into the ASP solver CLINGO, aiming to enhance reasoning with temporal operators for more effective handling of dynamic scenarios.
Temporal and dynamic extensions of Answer Set Programming (ASP) have played an important role in addressing dynamic problems, as they allow the use of temporal operators to reason with dynamic scenarios in a very effective way. In my Ph.D. research, I intend to exploit the relationship between automata theory and dynamic logic to add automata-based techniques to the ASP solver CLINGO helping us to deal with theses type of problems.