Nested Aggregates in Answer Sets: An Application to a Priori Optimization
This work addresses computational challenges in operations research by extending answer set programming with nested aggregates, though it appears incremental.
The paper introduces nested aggregates in answer set programming and optimization to handle complex constraints, applying it to the Probabilistic Traveling Salesman Problem to demonstrate feasibility.
We allow representing and reasoning in the presence of nested multiple aggregates over multiple variables and nested multiple aggregates over functions involving multiple variables in answer sets, precisely, in answer set optimization programming and in answer set programming. We show the applicability of the answer set optimization programming with nested multiple aggregates and the answer set programming with nested multiple aggregates to the Probabilistic Traveling Salesman Problem, a fundamental a priori optimization problem in Operation Research.