プランナ最適化問題：定式化とフレームワーク
The Planner Optimization Problem: Formulations and Frameworks
プランナの内部パラメータを問題インスタンスに応じて自動調整する「プランナ最適化問題」を統一的に定式化し、再利用可能なソフトウェアフレームワークOPOFを提案した。
著者: Yiyuan Lee, Katie Lee, Panpan Cai, David Hsu, Lydia E. Kavraki
分類: cs.AI, cs.RO
原文アブストラクト
Identifying internal parameters for planning is crucial to maximizing the performance of a planner. However, automatically tuning internal parameters which are conditioned on the problem instance is especially challenging. A recent line of work focuses on learning planning parameter generators, but lack a consistent problem definition and software framework. This work proposes the unified planner optimization problem (POP) formulation, along with the Open Planner Optimization Framework (OPOF), a highly extensible software framework to specify and to solve these problems in a reusable manner.
