Call for submissions: 9th workshop on Artificial Intelligence and Cognition

The main motivation for the AIC events lies in the fact that, historically, research in Artificial Intelligence has been based on a strong collaboration with other disciplines within the realm of the cognitive sciences.

Many of the original founders of AI as a research discipline aimed to develop human-level AI systems by taking inspiration from the heuristics of human cognition. This goal is still pursued (albeit with different interpretations) by many researchers around the world, and is one of the main challenges for the AI community. Indeed, the collaboration between AI and Cognitive Science has produced mutual benefits over the years.

In AI, this partnership has led to the realization of better intelligent systems. In cognitive science, in turn, this partnership has enabled the development of cognitive models and architectures that provide a better understanding of human reasoning.

In recent years, after a period of partial fragmentation of research directions, the area of cognitively inspired artificial systems is gradually attracting renewed attention from both academia and industry, and the awareness of the need for additional research in this interdisciplinary field has gained widespread acceptance.

We invite all researchers who are interested in the overall goal and the topics of interest (below) of the AIC workshop series to submit their scientific contributions to the AIC scientific journal. AIC is a peer-reviewed scientific venue that particularly welcome papers raising challenging questions, innovative ideas and out of the box thinking, which will hopefully promote interesting discussions at the workshop. The participation of early state researchers in particular is encouraged. Topics of interest for the AIC community include but are not limited to:

- Knowledge Representation and Cognition (e.g. Neural Networks models, Conceptual Spaces, Ontologies and representation of common sense)

- Cognitive Architectures (e.g. SOAR, ACT-R) and Cognitive modelling for Artificial Systems

- B.I.C.A. (Biologically Inspired Cognitive Architectures) and systems Cognitive Robotics

- Human Robot Interaction

- Commonsense Reasoning

- XAI-Explainable Artificial Intelligence

- Evaluation of cognitively driven AI systems compared with other AI approaches

- Cognition and Semantic Web

- Methodological open questions on AI and Cognition

- Automated reasoning: deductive, probabilistic, diagnostic, causal and analogical inference

- Historical and theoretical relation among Cognitive Science and Artificial Intelligence

- Knowledge discovery and acquisition

- Modelling of human learning and knowledge acquisition in complex domains

- Computational Linguistics, Natural Language Processing Understanding Logic and Reasoning

- Evolutionary Computation

- Spatial Cognition and Computation

- Cognitively inspired Machine Learning

- Computational Theories of Learning

- Computational Creativity

- Cognitive and the Moving Image

- Computational Models of Narrative Understanding (Visuo-Auditory Narrativity, Perception)

- Decision Support Systems

All submissions must be written in English and must be formatted according to the information for LNCS Authors. All papers must present original work that is not currently under review.

We welcome the following types of contributions:

- Full research papers (8 to 14 pages)

- Short research papers (4 to 7 pages)

- Extended abstracts of recently published journal papers (1 to 2 pages)

Full research paper submissions must describe original and completed work, with inclusion of mature results and evaluation. Short research paper submissions can present a work in progress/position paper or include a small focused contribution with preliminary results.

- Extended Abstract: Authors are invited to submit an extended abstract of their recently published journal articles within the field of AI and cognition. The original article should be accepted and published no earlier than 2022.

Please submit your contribution via EasyChair.