Expectation: Personalized Explainable Artificial Intelligence for Decentralized Agents with Heterogeneous Knowledge


Davide Calvaresi, Giovanni Ciatto, Amro Najjar, Reyhan Aydoğan, Leon Van der Torre, Andrea Omicini, Michael I. Schumacher  

Explainable AI (XAI) has emerged in recent years as a set of techniques and methodologies to interpret and explain machine learning (ML) predictors. To date, many initiatives have been proposed. Nevertheless, current research efforts mainly focus on methods tailored to specific ML tasks and algorithms, such as image classification and sentiment analysis. However, explanation techniques are still embryotic, and they mainly target ML experts rather than heterogeneous end-users. Furthermore, existing solutions assume data to be centralised, homogeneous, and fully/continuously accessible—circumstances seldom found altogether in practice. Arguably, a system-wide perspective is currently missing.

The project named “Personalized Explainable Artificial Intelligence for Decentralized Agents with Heterogeneous Knowledge ” (Expectation) aims at overcoming such limitations. This manuscript presents the overall objectives and approach of the Expectation project, focusing on the theoretical and practical advance of the state of the art of XAI towards the construction of personalised explanations in spite of decentralisation and heterogeneity of knowledge, agents, and explainees (both humans or virtual).

To tackle the challenges posed by personalisation, decentralisation, and heterogeneity, the project fruitfully combines abstractions, methods, and approaches from the multi-agent systems, knowledge extraction/injection, negotiation, argumentation, and symbolic reasoning communities.

(keywords) Multi-agent systems; eXplanable AI; Chist-Era IV; Personalisation; Decentralisation; Expectation

Explainable and Transparent AI and Multi-Agent Systems. Third International Workshop, EXTRAAMAS 2021, Virtual Event, May 3–7, 2021, Revised Selected Papers, Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence) 12688, pages 331-343,  2021.
Davide Calvaresi, Amro Najjar, Michael Winikoff, Kary Främling (eds.), Springer Nature.

@incollection{expectation-extraamas2021,
address = {Basel, Switzerland},
author = {Calvaresi, Davide and Ciatto, Giovanni and Najjar, Amro and Aydo{\u g}an, Reyhan and Van der Torre, Leon and Omicini, Andrea and Schumacher, Michael I.},
booktitle = {Explainable and Transparent AI and Multi-Agent Systems. Third International Workshop, EXTRAAMAS 2021, Virtual Event, May 3--7, 2021, Revised Selected Papers},
doi = {10.1007/978-3-030-82017-6_20},
editor = {Calvaresi, Davide and Najjar, Amro and Winikoff, Michael and Fr{\"a}mling, Kary},
isbn = {978-3-030-82016-9},
isbn-online = {978-3-030-82017-6},
issn = {0302-9743},
keywords = {Multi-agent systems; eXplanable AI; Chist-Era IV; Personalisation; Decentralisation; Expectation},
pages = {331--343},
publisher = {Springer Nature},
series = {Lecture Notes in Computer Science},
subseries = {Lecture Notes in Artificial Intelligence},
title = {{{\sc Expectation}}: Personalized Explainable Artificial Intelligence for Decentralized Agents with Heterogeneous Knowledge},
url = {http://link.springer.com/10.1007/978-3-030-82017-6_20},
volume = 12688,
year = 2021}

    

Publication

Expectation: Personalized Explainable Artificial Intelligence for Decentralized Agents with Heterogeneous Knowledge

— status

published  

— authors

Davide Calvaresi, Giovanni Ciatto, Amro Najjar, Reyhan Aydoğan, Leon Van der Torre, Andrea Omicini, Michael I. Schumacher

— editors

Davide Calvaresi, Amro Najjar, Michael Winikoff, Kary Främling

URLs & IDs

original page

— DOI

10.1007/978-3-030-82017-6_20

— DBLP

conf/atal/CalvaresiCNATO021

— print ISSN

0302-9743

— online ISSN

1611-3349

— print ISBN

978-3-030-82016-9

— online ISBN

978-3-030-82017-6

BibTeX

— BibTeX ID
expectation-extraamas2021
— BibTeX category
incollection

APICe

— event
EXTRAAMAS 2021
— journal/series
LNCS

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