This is an implementation of AC-Band, an algorithm configurator described in the paper AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration.
We study the algorithm configuration (AC) problem, in which one seeks to find an optimal parameter configuration of a given target algorithm in an automated way. Recently, there has been significant progress in designing AC approaches that satisfy strong theoretical guarantees. However, a significant gap still remains between the practical performance of these approaches and state-of-the-art heuristic methods. To this end, we introduce AC-Band, a general approach for the AC problem based on multi-armed bandits that provides theoretical guarantees while exhibiting strong practical performance. We show that AC-Band requires significantly less computation time than other AC approaches providing theoretical guarantees while still yielding high-quality configurations.
Python 3, numpy, matplotlib
The saved runtimes of the CPLEX integer progarm solver on two datsets (Regions, RCW) can be downloaded here and the saved runtimes of Minisat sat solver on the CNFuzzdd data can be downloaded from this repo. The runtime environments are obtained from here and here
# Main experiments
python run_ac_band_[rcw|region|sat].py