Activity, Plan, and Goal Recognition: A Review.
Activity, Plan, and Goal Recognition: A Review.
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DOI：
10.3389/frobt.2021.643010
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发表时间：
2021
影响因子：
3.4
通讯作者：
Peer A
中科院分区：
文献类型：
--
作者：
Van-Horenbeke FA;Peer A
在不受约束的环境中识别人的行动、计划和目标是未来机器人系统实现自然人机交互所需的关键功能。事实上，我们人类不断地理解和预测他人的行动和目标，这使我们能够以直观和安全的方式进行互动。虽然行动和计划识别是人类自然执行的任务，几乎不费力气，但从人工智能的角度来看，它们仍然是一个悬而未决的问题。在不受约束的环境中可能会遇到各种各样的行动和计划，这使得目前的方法远远达不到人类的表现。此外，虽然已经提出了非常不同类型的算法来解决活动、计划和目标(意图)识别问题，但这些算法往往只关注问题的一个部分(例如，动作识别)，并且还没有那么彻底地探索解决整个问题的技术。这篇综述旨在提供对活动、计划和目标识别问题的总体看法。它从人类的角度和计算的角度对问题进行了描述，并提出了解决问题的主要类型的方法(基于逻辑的、经典的机器学习、深度学习和大脑启发)的分类，以及对这些类别的描述和比较。这种对这一问题的总体看法有助于确定研究差距，也可能为开发以统一方式解决这一问题的新方法提供灵感。
Recognizing the actions, plans, and goals of a person in an unconstrained environment is a key feature that future robotic systems will need in order to achieve a natural human-machine interaction. Indeed, we humans are constantly understanding and predicting the actions and goals of others, which allows us to interact in intuitive and safe ways. While action and plan recognition are tasks that humans perform naturally and with little effort, they are still an unresolved problem from the point of view of artificial intelligence. The immense variety of possible actions and plans that may be encountered in an unconstrained environment makes current approaches be far from human-like performance. In addition, while very different types of algorithms have been proposed to tackle the problem of activity, plan, and goal (intention) recognition, these tend to focus in only one part of the problem (e.g., action recognition), and techniques that address the problem as a whole have been not so thoroughly explored. This review is meant to provide a general view of the problem of activity, plan, and goal recognition as a whole. It presents a description of the problem, both from the human perspective and from the computational perspective, and proposes a classification of the main types of approaches that have been proposed to address it (logic-based, classical machine learning, deep learning, and brain-inspired), together with a description and comparison of the classes. This general view of the problem can help on the identification of research gaps, and may also provide inspiration for the development of new approaches that address the problem in a unified way.
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影响因子：
2.8
作者：
Bouchard, Bruno;Giroux, Sylvain;Bouzouane, Abdenour
通讯作者：
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影响因子：
4.3
作者：
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DOI：
10.2478/v10023-007-0010-0
发表时间：
2007-12-01
影响因子：
0.4
作者：
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通讯作者：
Dreyfus, Hubert
影响因子：
3.6
作者：
Carberry, S
通讯作者：
Carberry, S