SteerBench: a benchmark suite for evaluating steering behaviors
SteerBench: a benchmark suite for evaluating steering behaviors
复制标题
DOI：
10.1002/cav.277
复制
发表时间：
2009-09
影响因子：
1.1
通讯作者：
Shawn Singh;Mubbasir Kapadia;P. Faloutsos;G. Reinman
中科院分区：
文献类型：
--
作者：
Shawn Singh;Mubbasir Kapadia;P. Faloutsos;G. Reinman
操纵是一项具有挑战性的任务，几乎所有虚拟世界中的代理都需要。有大量的和越来越多的方法转向，它是越来越重要的问一个基本的问题：我们如何才能客观地比较转向算法？据我们所知，没有标准的方法来评估或比较转向解决方案的质量。本文介绍了SteerBench：一个基准框架，用于客观地评估虚拟代理的转向行为。我们提出了一套不同的测试案例，评估指标，和评分方法，可用于比较不同的转向算法。我们的框架可以很容易地由用户定制，以评估特定的行为和新的测试用例。我们展示了我们的基准测试过程中的两个例子转向算法，显示从我们的指标获得的洞察力。我们希望这一框架能够发展成为指导评估的标准。版权所有© 2009约翰威利父子有限公司。
Steering is a challenging task, required by nearly all agents in virtual worlds. There is a large and growing number of approaches for steering, and it is becoming increasingly important to ask a fundamental question: how can we objectively compare steering algorithms? To our knowledge, there is no standard way of evaluating or comparing the quality of steering solutions. This paper presents SteerBench: a benchmark framework for objectively evaluating steering behaviors for virtual agents. We propose a diverse set of test cases, metrics of evaluation, and a scoring method that can be used to compare different steering algorithms. Our framework can be easily customized by a user to evaluate specific behaviors and new test cases. We demonstrate our benchmark process on two example steering algorithms, showing the insight gained from our metrics. We hope that this framework can grow into a standard for steering evaluation. Copyright © 2009 John Wiley & Sons, Ltd.