Abstract Variational quantum algorithms, a class of heuristics, are promising candidates for the demonstration useful computation. Finding best way to amplify performance these methods on hardware is an important task. Here, we evaluate optimization heuristics with existing techniques called “meta-learners.” We compare meta-learner evolutionary strategies, L-BFGS-B and Nelder-Mead approaches, t...

Symbolic search, using Binary Decision Diagrams (BDDs) to represent sets of states, is a competitive approach optimal planning. Yet heuristic search in this context remains challenging. The many advances on admissible planning heuristics are not directly applicable, as they evaluate one state at time. Indeed, progress functions symbolic has been limited and even very informed have shown be detr...