HUSCAP logo Hokkaido Univ. logo

Hokkaido University Collection of Scholarly and Academic Papers >
情報科学研究科  >
雑誌発表論文等  >

障害物密度に応じた迷路探索問題の難易度指標と実時間探索アルゴリズムの性能解析

フルテキスト
mizusawa2006jsai-final.pdf473.59 kBPDF見る/開く
この文献へのリンクには次のURLを使用してください:http://hdl.handle.net/2115/14559

タイトル: 障害物密度に応じた迷路探索問題の難易度指標と実時間探索アルゴリズムの性能解析
その他のタイトル: Hardness Measures for Maze Problems Parameterized by Obstacle Ratio and Performance Analysis of Real-Time Search Algorithms
著者: 水澤, 雅高 著作を一覧する
栗原, 正仁 著作を一覧する
キーワード: real-time search
maze problem
state space
heuristics
phase transitions
発行日: 2006年
出版者: 人工知能学会
誌名: 人工知能学会論文誌
巻: 21
号: 3
開始ページ: 266
終了ページ: 275
出版社 DOI: 10.1527/tjsai.21.266
抄録: Although the maze (or gridworld) is one of the most widely used benchmark problems for real-time search algorithms, it is not sufficiently clear how the difference in the density of randomly positioned obstacles affects the structure of the state spaces and the performance of the algorithms. In particular, recent studies of the so-called phase transition phenomena that could cause dramatic change in their performance in a relatively small parameter range suggest that we should evaluate the performance in a parametric way with the parameter range wide enough to cover potential transition areas. In this paper, we present two measures for characterizing the hardness of randomly generated mazes parameterized by obstacle ratio and relate them to the performance of real-time search algorithms. The first measure is the entropy calculated from the probability of existence of solutions. The second is a measure based on total initial heuristic error between the actual cost and its heuristic estimation. We show that the maze problems are the most complicated in both measures when the obstacle ratio is around 41%. We then solve the parameterized maze problems with the well-known real-time search algorithms RTA*, LRTA*, and MARTA* to relate their performance to the proposed measures. Evaluating the number of steps required for a single problem solving by the three algorithms and the number of those required for the convergence of the learning process in LRTA*, we show that they all have a peak when the obstacle ratio is around 41%. The results support the relevance of the proposed measures. We also discuss the performance of the algorithms in terms of other statistical measures to get a quantitative, deeper understanding of their behavior.
資料タイプ: article (author version)
URI: http://hdl.handle.net/2115/14559
出現コレクション:雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

提供者: 栗原 正仁

 

本サイトに関するご意見・お問い合わせは repo at lib.hokudai.ac.jp へお願いします。 - 北海道大学