Learning Robust Search Strategies Using a Bandit-Based Approach

Understand

Effective solving of constraint problems often requires choosing good or specific search heuristics.

• However, choosing or designing a good search heuristic is non-trivial and is often a manual process.
• In this paper, rather than manually choosing/designing search heuristics, we propose the use of bandit-based learning techniques to automatically select search heuristics.
• Our approach is online where the solver learns and selects from a set of heuristics during search.