Abstract

In the present article the authors introduce procedures to generate multiple alternative encodings, identical to the original encoding, to enhance encoding diversity. The procedures to generate multiple alternative encodings, identical to the original encoding, to enhance encoding diversity. System capable of taking a set of problem encodings, problem instances, and an ASP grounding solving system as inputs, automatically generating equivalent encodings. As new instances arise, the system selects the encoding expected to perform best for each instance, enabling more efficient ASP solving. The system supports both planned and interleaved execution of encodings, complementing machine learning methods. This approach can be extended to identify challenging instances for other combinatorial problems, further enhancing the utility of our framework