On the Design of PSyKI: a Platform for Symbolic Knowledge Injection into Sub-Symbolic Predictors


Matteo Magnini, Giovanni Ciatto, Andrea Omicini

Explainable and Transparent AI and Multi-Agent Systems, Ch. 6, pages 90–108
Lecture Notes in Computer Science 13283,  2022
Springer
Davide Calvaresi, Amro Najjar, Michael Winikoff, Kary Främling (eds.)
4th International Workshop, EXTRAAMAS 2022, Virtual Event, May 9–10, 2022, Revised Selected Papers

A long-standing ambition in artificial intelligence is to integrate predictors' inductive features (i.e., learning from examples) with deductive capabilities (i.e., drawing inferences from prior symbolic knowledge). Many algorithms methods in the literature support injection of prior symbolic knowledge into predictors, generally following the purpose of attaining better (i.e., more effective or efficient w.r.t. predictive performance) predictors. However, to the best of our knowledge, running implementations of these algorithms are currently either proof of concepts or unavailable in most cases. Moreover, an unified, coherent software framework supporting them as well as their interchange, comparison and exploitation in arbitrary ML workflows is currently missing. Accordingly, in this paper we present PSyKI, a platform providing general-purpose support to symbolic knowledge injection into predictors via different algorithms.

(keywords) Symbolic Knowledge Injection,  Explainable AI, XAI, Neural Networks, PSyKI
 @incollection{psyki-extraamas2022,
author = {Magnini, Matteo and Ciatto, Giovanni and Omicini, Andrea},
booktitle = {Explainable and Transparent AI and Multi-Agent Systems},
chapter = 6,
doi = {10.1007/978-3-031-15565-9_6},
editor = {Calvaresi, Davide and Najjar, Amro and Winikoff, Michael and Fr{\"a}mling, Kary},
isbn = {978-3-031-15564-2},
keywords = {Symbolic Knowledge Injection, Explainable AI, XAI, Neural Networks, PSyKI},
note = {4th International Workshop, EXTRAAMAS 2022, Virtual Event, May 9--10, 2022, Revised Selected Papers},
pages = {90--108},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {On the Design of {PSyKI}: a Platform for Symbolic Knowledge Injection into Sub-Symbolic Predictors},
url = {https://link.springer.com/chapter/10.1007/978-3-031-15565-9_6},
url-pdf = {https://link.springer.com/content/pdf/10.1007/978-3-031-15565-9_6.pdf},
volume = 13283,
year = 2022

Talks

Journals & Series

Events

  • EXplainable and TRAnsparent AI and Multi-Agent Systems: Fourth International Workshop (EXTRAAMAS 2022) — 09/05/2022–10/05/2022

Publication

— authors

Matteo Magnini, Giovanni Ciatto, Andrea Omicini

— editors

Davide Calvaresi, Amro Najjar, Michael Winikoff, Kary Främling

— status

published

— sort

paper in proceedings

Venue

— volume

Explainable and Transparent AI and Multi-Agent Systems

— series

Lecture Notes in Computer Science

— volume

13283

— chapter

6

— pages

90–108

— publication date

2022

URLs

original page

Identifiers

— DOI

10.1007/978-3-031-15565-9_6

— DBLP

conf/atal/MagniniCO22

— IRIS

11585/899511

— Scholar

7587528289517313138

— Scopus

2-s2.0-85138317005

— WoS / ISI

000870042100006

— print ISSN

0302-9743

— online ISSN

1611-3349

— print ISBN

978-3-031-15564-2

— online ISBN

978-3-031-15565-9

BibTeX

— BibTeX ID
psyki-extraamas2022
— BibTeX category
incollection

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