Item Type |
Conference or Workshop Item
(Poster)
|
Abstract |
The increasing complexity of Cyber-Physical Systems (CPS) increases
the difficulty for users to understand their behavior. Using
existing Explainable Artificial Intelligence (XAI) methods, CPS can
explain their behavior to the users. However, the input-output correlations
used in XAI methods are not capable of explaining certain
anomalies in CPS behavior caused by contextual influences (CIs)
since they do not consider the context of the CPS. Some well-known
techniques used for understanding such CIs on CPS are test chambers
and the analysis of logged CPS data. However, test chambers
are typically only available to the manufacturer of a CPS, thus
not useful for understanding CIs on the shop floors. Data analysis
methods focus on data correlations, which are insufficient to explain
causal relationships without using expert (human) knowledge.
Hence, we propose a context-aware log-based explanation system
to explain the causal relationship between CIs and the behavior of
a CPS. The proposed solution employs semantic technologies to
access the context of the CPS. It demonstrates the causal relationship
between the CPS and CIs through counterfactual explanation
and abductive reasoning methods. The contextual explanations offered
by the proposed system will assist users in visualizing diverse
scenarios in order to improve the CPS’ behavior accordingly. |
Authors |
Jha, Sanjiv; Mayer, Simon & Garcia, Kimberly |
Journal or Publication Title |
11th International Conference on the Internet of Things (IoT ’21) |
Language |
English |
Subjects |
computer science |
Refereed |
Yes |
Date |
11 November 2021 |
Publisher |
ACM |
Place of Publication |
St.Gallen, Switzerland |
Number of Pages |
4 |
Publisher DOI |
https: //doi.org/10.1145/3494322.3494359 |
Contact Email Address |
sanjiv.jha@unisg.ch |
Depositing User |
Sanjiv Jha
|
Date Deposited |
07 Jan 2022 12:23 |
Last Modified |
20 Jul 2022 17:47 |
URI: |
https://www.alexandria.unisg.ch/publications/265539 |