Abstract
Goal recognition aims to recognize the set of candidate goals that are compatible with the observed behavior of an agent. In this paper, we develop a method based on the operatorcounting framework that efficiently computes solutions that satisfy the observations and uses the information generated to solve goal recognition tasks. Our method reasons explicitly about both partial and noisy observations: estimating uncertainty for the former, and satisfying observations given the unreliability of the sensor for the latter. We evaluate our approach empirically over a large data set, analyzing its components on how each can impact the quality of the solutions. In general, our approach is superior to previous methods in terms of agreement ratio, accuracy, and spread. Finally, our approach paves the way for new research on combinatorial optimization to solve goal recognition tasks.
| Original language | English |
|---|---|
| Title of host publication | 35th AAAI Conference on Artificial Intelligence (AAAI 2021) |
| Subtitle of host publication | Volume 13: AAAI Technical Tracks |
| Publisher | Association for the Advancement of Artificial Intelligence |
| Pages | 11939-11946 |
| Number of pages | 8 |
| Volume | 35(13) Part 1 |
| ISBN (Electronic) | 9781713835974 |
| DOIs | |
| Publication status | Published - 18 May 2021 |
| Event | 35th AAAI Conference on Artificial Intelligence, AAAI 2021 - Virtual, Online Duration: 2 Feb 2021 → 9 Feb 2021 |
Publication series
| Name | 35th AAAI Conference on Artificial Intelligence, AAAI 2021 |
|---|---|
| Number | 13 |
| Volume | 35 |
| ISSN (Print) | 2159-5399 |
| ISSN (Electronic) | 2374-3468 |
Conference
| Conference | 35th AAAI Conference on Artificial Intelligence, AAAI 2021 |
|---|---|
| City | Virtual, Online |
| Period | 2/02/21 → 9/02/21 |
Bibliographical note
Funding Information:Felipe Meneguzzi acknowledges support from CNPq with projects 407058/2018-4 (Universal) and 302773/2019-3 (PQ Fellowship). André G. Pereira acknowledges support from FAPERGS with project 17/2551-0000867-7. This study was financed in part by the Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Ramon Fraga Pereira acknowledges support from the ERC Advanced Grant WhiteMech (No. 834228) and the EU ICT-48 2020 project TAILOR (No. 952215).
Keywords
- Activity and Plan Recognition