Abstract
Goal Recognition is the task of inferring an agent's goal, from a set of hypotheses, given a model of the environment dynamic, and a sequence of observations of such agent's behavior. While research on this problem gathered momentum as an offshoot of plan recognition, recent research has established it as a major subject of research on its own, leading to numerous new approaches that both expand the expressivity of domains in which to perform goal recognition and substantial advances to the state-of-the-art on established domain types. In this survey, we focus on the advances to goal recognition achieved in the last decade, categorizing the resulting techniques and identifying a number of opportunities for further breakthrough research.
Original language | English |
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Title of host publication | Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 |
Editors | Zhi-Hua Zhou |
Publisher | International Joint Conferences on Artificial Intelligence Organization |
Pages | 4524-4532 |
Number of pages | 9 |
ISBN (Electronic) | 9780999241196 |
DOIs | |
Publication status | Published - 19 Aug 2021 |
Event | 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 - Virtual, Online, Canada Duration: 19 Aug 2021 → 27 Aug 2021 |
Publication series
Name | IJCAI International Joint Conference on Artificial Intelligence |
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ISSN (Print) | 1045-0823 |
Conference
Conference | 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 |
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Country/Territory | Canada |
City | Virtual, Online |
Period | 19/08/21 → 27/08/21 |
Bibliographical note
Funding Information:Felipe Meneguzzi acknowledges support from CNPq with projects 407058/2018-4 (Universal) and 302773/2019-3 (PQ Fellowship). Ramon Fraga Pereira acknowledges support from the ERC Advanced Grant WhiteMech (No. 834228) and the EU ICT-48 2020 project TAILOR (No. 952215). We acknowledge the valuable input provided by the anonymous IJCAI reviewers, which greatly improved this survey.