Abstract:
In this paper, we propose the use of schemata bandits for
optimization. This technique is a subclass of hierarchical
bandits where the bandits are schemata. We investigate its
use on a benchmark of binary combinatorial optimization
problems, the Maximum Satisfiability (MAXSAT) problem.
We compare performance with hierarchical Bayesian Opti-
mization Algorithms (hBOAs) namely GSAT and WALK-
SAT. Results suggest that using a bandit strategy enhances
solver performance
