作者: Ariel Felner , Roni Stern , Daniel Gilon
DOI:
关键词: Product (mathematics) 、 Mathematical optimization 、 Real-time computing 、 Enhanced Data Rates for GSM Evolution 、 Bounded function 、 Mathematics
摘要: Potential Search (PS) is an algorithm that designed to solve bounded cost search problems. In this paper, we modify PS work within the framework of suboptimal and introduce Dynamic (DPS). DPS uses idea but modifies bound be product minimal f-value in OPEN required bound. We study its attributes. then experimentally compare WA* EES on a variety domains parameters affect behavior these algorithms.In general show with unit edge costs (e.g., many standard benchmarks) significantly outperforms there are exceptions.