| Title | A Decentralized Approach to Explanatory Artificial Intelligence for Autonomic Systems |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Houzé, É, Diaconescu, A., Dessalles, J.-L., Mengay, D., Schumann, M. |
| Conference Name | 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) |
| Keywords | artificial intelligence, Autonomic Management, autonomic management system, Autonomic systems, black box methods, Cognition, Cyber-physical systems, D-CAN, Decentralised Architecture, explanation, explanatory AI, explanatory artificial intelligence, fault tolerant computing, generic decentralized architecture, home automation, Power demand, pubcrawl, Resiliency, Runtime, Scalability, SISSY systems, smart home, smart home domain, Smart homes, user trust, xai, XAI functions, XAI solution |
| Abstract | While Explanatory AI (XAI) is attracting increasing interest from academic research, most AI-based solutions still rely on black box methods. This is unsuitable for certain domains, such as smart homes, where transparency is key to gaining user trust and solution adoption. Moreover, smart homes are challenging environments for XAI, as they are decentralized systems that undergo runtime changes. We aim to develop an XAI solution for addressing problems that an autonomic management system either could not resolve or resolved in a surprising manner. This implies situations where the current state of affairs is not what the user expected, hence requiring an explanation. The objective is to solve the apparent conflict between expectation and observation through understandable logical steps, thus generating an argumentative dialogue. While focusing on the smart home domain, our approach is intended to be generic and transferable to other cyber-physical systems offering similar challenges. This position paper focuses on proposing a decentralized algorithm, called D-CAN, and its corresponding generic decentralized architecture. This approach is particularly suited for SISSY systems, as it enables XAI functions to be extended and updated when devices join and leave the managed system dynamically. We illustrate our proposal via several representative case studies from the smart home domain. |
| DOI | 10.1109/ACSOS-C51401.2020.00041 |
| Citation Key | houze_decentralized_2020 |
A Decentralized Approach to Explanatory Artificial Intelligence for Autonomic Systems