Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Apr 26:5:806262.
doi: 10.3389/frai.2022.806262. eCollection 2022.

Intention Recognition With ProbLog

Gary B Smith  1   2   3 , Vaishak Belle  2   3 , Ronald P A Petrick  1   4
Affiliations

Intention Recognition With ProbLog

Gary B Smith et al. Front Artif Intell. .

Abstract

In many scenarios where robots or autonomous systems may be deployed, the capacity to infer and reason about the intentions of other agents can improve the performance or utility of the system. For example, a smart home or assisted living facility is better able to select assistive services to deploy if it understands the goals of the occupants in advance. In this article, we present a framework for reasoning about intentions using probabilistic logic programming. We employ ProbLog, a probabilistic extension to Prolog, to infer the most probable intention given observations of the actions of the agent and sensor readings of important aspects of the environment. We evaluated our model on a domain modeling a smart home. The model achieved 0.75 accuracy at full observability. The model was robust to reduced observability.

Keywords: assisted living at home; goal recognition; intention recognition; probabilistic logic programming; smart home.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Comparing intention, plan, and activity recognition.
Figure 2
Figure 2
Kitchen example graph structure.
Figure 3
Figure 3
Model development process.
See this image and copyright information in PMC

References

    1. Acampora G., Cook D. J., Rashidi P., Vasilakos A. V. (2013). A survey on ambient intelligence in healthcare. Proc. IEEE 101, 2470–2494. 10.1109/JPROC.2013.2262913 - DOI - PMC - PubMed
    1. Acciaro G. D., D'Asaro F. A., Rossi S. (2021). Predicting humans: a sensor-based architecture for real time Intent Recognition using Problog.
    1. Bisson F., Larochelle H., Kabanza F. (2015). “Using a recursive neural network to learn an agent's decision model for plan recognition,” in Twenty-Fourth International Joint Conference on Artificial Intelligence (Buenos Aires: ).
    1. Bratko I.. (2001). Prolog Programming for Artificial Intelligence. Harlow: Pearson Education.
    1. Cheek P., Nikpour L., Nowlin H. D. (2005). Aging well with smart technology. Nurs. Administrat. Q. 29, 329–338. 10.1097/00006216-200510000-00007 - DOI - PubMed

LinkOut - more resources