Divide-and-Conquer Frontier Search Applied to Optimal Sequence Alignment

We present a new algorithm that reduces the space complexity of heuristic search. It is most effective for problem spaces that grow polynomially with problem size, but contain large numbers of short cycles. For example, the problem of finding an optimal global alignment of several DNA or amino-acid sequences can be solved by finding a lowest-cost corner-tocorner path in a -dimensional grid. A previous algorithm, called divide-and-conquer bidirectional search (Korf 1999), saves memory by storing only the Open lists and not the Closed lists. We show that this idea can be applied in a unidirectional search as well. This extends the technique to problems where bidirectional search is not applicable, and is more efficient in both time and space than the bidirectional version. If

• Type: Conference
• Year: 2000
• Where: AAAI
• Authors: Richard E. Korf, Weixiong Zhang
• Keywords: AAAI 2000, Bidirectional Search, Divide-and-conquer Bidirectional Search, Intelligent Agents, Optimal Global Alignment