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Temporal Models for History-Aware Explainability

Ullauri, Juan Marcelo Parra; García-Domínguez, Antonio; Paucar, Luis Hernán García; Bencomo, Nelly


Juan Marcelo Parra Ullauri

Antonio García-Domínguez

Luis Hernán García Paucar


Abdelouahed Gherbi

Wahab Hamou-Lhadj

Ahmed Bali


On one hand, there has been a growing interest towards the application of AI-based learning and evolutionary programming for self-adaptation under uncertainty. On the other hand, self-explanation is one of the self-* properties that has been neglected. This is paradoxical as self-explanation is inevitably needed when using such techniques. In this paper, we argue that a self-adaptive autonomous system (SAS) needs an infrastructure and capabilities to be able to look at its own history to explain and reason why the system has reached its current state. The infrastructure and capabilities need to be built based on the right conceptual models in such a way that the system's history can be stored, queried to be used in the context of the decision-making algorithms.

The explanation capabilities are framed in four incremental levels, from forensic self-explanation to automated history-aware (HA) systems. Incremental capabilities imply that capabilities at Level n should be available for capabilities at Level n + 1. We demonstrate our current reassuring results related to Level 1 and Level 2, using temporal graph-based models. Specifically, we explain how Level 1 supports forensic accounting after the system's execution. We also present how to enable on-line historical analyses while the self-adaptive system is running, underpinned by the capabilities provided by Level 2. An architecture which allows recording of temporal data that can be queried to explain behaviour has been presented, and the overheads that would be imposed by live analysis are discussed. Future research opportunities are envisioned.


Ullauri, J. M. P., García-Domínguez, A., Paucar, L. H. G., & Bencomo, N. (2020). Temporal Models for History-Aware Explainability. In A. Gherbi, W. Hamou-Lhadj, & A. Bali (Eds.), .

Conference Name SAM '20: 12th System Analysis and Modelling Conference
Conference Location (Online) Canada
Start Date Oct 19, 2020
End Date Oct 20, 2020
Publication Date 2020
Deposit Date Sep 25, 2022
Pages 155-164
ISBN 978-1-4503-8140-6
Public URL