Intelligent problem-solving as integrated hierarchical reinforcement learning

M Eppe, C Gumbsch, M Kerzel, PDH Nguyen… - Nature Machine …, 2022 - nature.com
According to cognitive psychology and related disciplines, the development of complex
problem-solving behaviour in biological agents depends on hierarchical cognitive …

[HTML][HTML] Using ontologies to enhance human understandability of global post-hoc explanations of black-box models

R Confalonieri, T Weyde, TR Besold… - Artificial Intelligence, 2021 - Elsevier
The interest in explainable artificial intelligence has grown strongly in recent years because
of the need to convey safety and trust in the 'how'and 'why'of automated decision-making to …

Artificial intelligence, artists, and art: attitudes toward artwork produced by humans vs. artificial intelligence

JW Hong, NM Curran - ACM Transactions on Multimedia Computing …, 2019 - dl.acm.org
This study examines how people perceive artwork created by artificial intelligence (AI) and
how presumed knowledge of an artist's identity (Human vs. AI) affects individuals' evaluation …

PopBlends: Strategies for conceptual blending with large language models

S Wang, S Petridis, T Kwon, X Ma… - Proceedings of the 2023 …, 2023 - dl.acm.org
Pop culture is an important aspect of communication. On social media people often post pop
culture reference images that connect an event, product or other entity to a pop culture …

Entrepreneurial action, creativity, & judgment in the age of artificial intelligence

DM Townsend, RA Hunt - Journal of Business Venturing Insights, 2019 - Elsevier
The rapid advancement of computationally complex systems of artificial intelligence (AI), is
the fruit of a decades-long effort to endow machines with cognitive capabilities that equal or …

A commonsense reasoning framework for explanatory emotion attribution, generation and re-classification

A Lieto, GL Pozzato, S Zoia, V Patti… - Knowledge-Based Systems, 2021 - Elsevier
Abstract We present DEGARI (Dynamic Emotion Generator And ReclassIfier), an
explainable system for emotion attribution and recommendation. This system relies on a …

The embodied crossmodal self forms language and interaction: a computational cognitive review

F Röder, O Özdemir, PDH Nguyen, S Wermter… - Frontiers in …, 2021 - frontiersin.org
Human language is inherently embodied and grounded in sensorimotor representations of
the self and the world around it. This suggests that the body schema and ideomotor action …

A description logic framework for commonsense conceptual combination integrating typicality, probabilities and cognitive heuristics

A Lieto, GL Pozzato - Journal of Experimental & Theoretical …, 2020 - Taylor & Francis
We propose a nonmonotonic Description Logic of typicality able to account for the
phenomenon of the combination of prototypical concepts. The proposed logic relies on the …

Trepan reloaded: A knowledge-driven approach to explaining black-box models

R Confalonieri, T Weyde, TR Besold… - ECAI 2020, 2020 - ebooks.iospress.nl
Abstract Explainability in Artificial Intelligence has been revived as a topic of active research
by the need to demonstrate safety to users and gain their trust in the 'how'and 'why'of …

Image schema combinations and complex events

MM Hedblom, O Kutz, R Peñaloza, G Guizzardi - KI-Künstliche Intelligenz, 2019 - Springer
Formal knowledge representation struggles to represent the dynamic changes within
complex events in a cognitively plausible way. Image schemas, on the other hand, are …