A Parallel Memory-efficient Epistemic Logic Program Solver: Harder, Better, Faster
This work addresses a critical bottleneck for researchers and practitioners using epistemic specifications in answer set programming, enabling more efficient solving of complex problems.
The authors tackled the exponential memory growth problem in solving epistemic logic programs (ELPs) by developing a new solver that reduces memory needs and improves speed, achieving better performance without exponential scaling with modal operators.
As the practical use of answer set programming (ASP) has grown with the development of efficient solvers, we expect a growing interest in extensions of ASP as their semantics stabilize and solvers supporting them mature. Epistemic Specifications, which adds modal operators K and M to the language of ASP, is one such extension. We call a program in this language an epistemic logic program (ELP). Solvers have thus far been practical for only the simplest ELPs due to exponential growth of the search space. We describe a solver that is able to solve harder problems better (e.g., without exponentially-growing memory needs w.r.t. K and M occurrences) and faster than any other known ELP solver.