The 2023 International Planning Competition

IF 2.5 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ai Magazine Pub Date : 2024-04-05 DOI:10.1002/aaai.12169
Ayal Taitler, Ron Alford, Joan Espasa, Gregor Behnke, Daniel Fišer, Michael Gimelfarb, Florian Pommerening, Scott Sanner, Enrico Scala, Dominik Schreiber, Javier Segovia-Aguas, Jendrik Seipp
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引用次数: 0

Abstract

In this article, we present an overview of the 2023 International Planning Competition. It featured five distinct tracks designed to assess cutting-edge methods and explore the frontiers of planning within these settings: the classical (deterministic) track, the numeric track, the Hierarchical Task Networks (HTN) track, the learning track, and the probabilistic and reinforcement learning track. Each of these tracks evaluated planning methodologies through one or more subtracks, with the goal of pushing the boundaries of current planner performance. To achieve this objective, the competition introduced a combination of well-established challenges and entirely novel ones. Within this article, each track offers an exploration of its historical context, justifies its relevance within the planning landscape, discusses emerging domains and trends, elucidates the evaluation methodology, and ultimately presents the results.

2023 年国际规划竞赛
本文概述了 2023 年国际规划竞赛。该竞赛有五个不同的赛道,旨在评估前沿方法并探索这些环境下的规划前沿:经典(确定性)赛道、数字赛道、分层任务网络(HTN)赛道、学习赛道以及概率和强化学习赛道。每个赛道都通过一个或多个子赛道对规划方法进行评估,目标是突破当前规划器性能的极限。为实现这一目标,比赛引入了成熟挑战和全新挑战的组合。在本文中,每个赛道都对其历史背景进行了探讨,证明了其在规划领域的相关性,讨论了新兴领域和趋势,阐明了评估方法,并最终给出了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ai Magazine
Ai Magazine 工程技术-计算机:人工智能
CiteScore
3.90
自引率
11.10%
发文量
61
审稿时长
>12 weeks
期刊介绍: AI Magazine publishes original articles that are reasonably self-contained and aimed at a broad spectrum of the AI community. Technical content should be kept to a minimum. In general, the magazine does not publish articles that have been published elsewhere in whole or in part. The magazine welcomes the contribution of articles on the theory and practice of AI as well as general survey articles, tutorial articles on timely topics, conference or symposia or workshop reports, and timely columns on topics of interest to AI scientists.
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