Volume •Abstracts •Preface •Authors •Program Committee •Keywords •BibTex Entries

GCAI 2020. 6th Global Conference on Artificial Intelligence (GCAI 2020)

Editors: Gregoire Danoy, Jun Pang and Geoff Sutcliffe

EPiC Series in Computing•Volume 72

9 articles•120 pages•Published: April 27, 2020

Papers

Learning Ex Nihilo

Selmer Bringsjord, Naveen Sundar Govindarajulu, John Licato and Michael Giancola

Pages 1-27

Adjudication of Symbolic & Connectionist Arguments in Autonomous Driving AI

Michael Giancola, Selmer Bringsjord, Naveen Sundar Govindarajulu and John Licato

Pages 28-33

Partial Regularization of First-Order Resolution Proofs

Jan Gorzny, Ezequiel Postan and Bruno Woltzenlogel Paleo

Pages 34-45

WinoReg: A New Faster and More Accurate Metric of Hardness for Winograd Schemas

Nicos Isaak and Loizos Michael

Pages 46-58

Face Image Deblurring: A Data-Driven Strategy

Abdelwahed Nahli, Yuanzhouhan Cao and Shugong Xu

Pages 59-69

Property Preserving Embedding of First-order Logic

Julian Parsert, Stephanie Autherith and Cezary Kaliszyk

Pages 70-82

Common Knowledge in an Epistemic Logic with Hypotheses

Levan Uridia and Dirk Walther

Pages 83-91

Guided Inductive Logic Programming: Cleaning Knowledge Bases with Iterative User Feedback

Yan Wu, Jinchuan Chen, Plarent Haxhidauti, Vinu Ellampallil Venugopal and Martin Theobald

Pages 92-106

Topical Neural Theorem Prover that Induces Rules

Shuang Xia, Krysia Broda and Alessandra Russo

Pages 107-120

Keyphrases

Argumentation, automated reasoning, computer vision, data cleaning, deep learning, Distributive knowledge, embedding, Evaluation of AI systems, feedback, first-order logic², High-Expressivity Planner, Hybrid, Hybrid AI, knowledge bases, knowledge representation, Kripke completeness, logical properties, machine learning, modal logic, Multi-Operator Logic, Natural language systems and linguistics, Neural Embedding, neural theorem prover, neural-symbolic integration, Proof Compression, resolution, rule induction, rule learning, supervised learning, topic, Uncertainty Multi-Operator Logic, unification, unsupervised learning, Winograd Schema Challenge