Beam Search: Faster and Monotonic
This work addresses heuristic search problems by providing incremental improvements to beam search for easier use and enhanced performance.
The paper tackled the problem of making beam search more practical by ensuring monotonicity in solution cost with increasing beam width and improving solution quality and speed using distance-to-go estimates in non-uniform cost domains, resulting in easier parameter tuning and faster, better solutions.
Beam search is a popular satisficing approach to heuristic search problems that allows one to trade increased computation time for lower solution cost by increasing the beam width parameter. We make two contributions to the study of beam search. First, we show how to make beam search monotonic; that is, we provide a new variant that guarantees non-increasing solution cost as the beam width is increased. This makes setting the beam parameter much easier. Second, we show how using distance-to-go estimates can allow beam search to find better solutions more quickly in domains with non-uniform costs. Together, these results improve the practical effectiveness of beam search.