不適切フィルタ縮約:振る舞いを変えてもサイズを削る組合せフィルタの自動縮約
Improper Filter Reduction
組合せフィルタを目標サイズ以下に自動縮約する問題を定式化し、振る舞いの差を測る2つの距離指標と動的計画法、NP困難性を示した上で、貪欲法とランダム化グローバル法の2つのヒューリスティックを提案・実験した論文。
著者: Fatemeh Zahra Saberifar, Ali Mohades, Mohammadreza Razzazi, Jason M. O'Kane
分類: cs.RO, cs.FL
原文アブストラクト
Combinatorial filters have been the subject of increasing interest from the robotics community in recent years. This paper considers automatic reduction of combinatorial filters to a given size, even if that reduction necessitates changes to the filter's behavior. We introduce an algorithmic problem called improper filter reduction, in which the input is a combinatorial filter F along with an integer k representing the target size. The output is another combinatorial filter F' with at most k states, such that the difference in behavior between F and F' is minimal. We present two metrics for measuring the distance between pairs of filters, describe dynamic programming algorithms for computing these distances, and show that improper filter reduction is NP-hard under these metrics. We then describe two heuristic algorithms for improper filter reduction, one greedy sequential approach, and one randomized global approach based on prior work on weighted improper graph coloring. We have implemented these algorithms and analyze the results of three sets of experiments.
関連論文
- 効率的に最小化可能な組合せフィルタの一般クラス組合せフィルタ
- ロボット向け組合せフィルタにおける出力確定性を課した非決定性組合せフィルタ
