Forthcoming Special Issues

29 August 2022

Foundations of Deep Learning

The rise of machine learning based techniques in cognitive neuroscience raises new philosophical and methodological questions about artificial cognitive systems and their bearing on biological cognitive systems. We seek papers from all related fields – cognitive science, philosophy, AI, neuroscience - that try to answer questions about the nature of learning, including but not limited to abstraction, imagination, sub-symbolic computing, miscomputation/adversarial challenges, machine sentience etc

Guest Editors:

Dr Brendan Ritchie, National Institutes of Health (NIH), USA
Associate Professor Matteo Colombo, Tilburg University, Netherlands

Special issue information:

Papers are welcomed from contributors from around the world, and we welcome Original Research and Review papers.

Original Research papers make an original contribution to the literature in Cognitive Systems Research. They may be purely theoretical, philosophical or a mix of empirical and theoretical research. Articles with predominantly empirical or formal contributions should have extended introduction and discussion sections explaining the theoretical contributions of the work to cognitive systems theory (i.e. why should other researchers in cognitive systems research care?). Papers that focus solely on computational methodologies, rather than a combination of methodologies (ie. experimental and computational) are not encouraged. Papers should be written in such a way that the research is accessible to an interdisciplinary audience. Recommended length is between 3,500 and 10,000 words (including abstract, but not excluding references).

Both Systematic and Literature Reviews are welcomed that provide a thorough analysis of the research around a specific topic. Reviews should offer a balanced account of newly emerging or rapidly progressing topics in cognitive science and related fields and provide a guide to both the most recent research as well as identifying trends for future research. Reviews may also provide readers guidance to a new problem or methodological issues within cognitive systems research. Recommended length is between 3,500 and 4,500 words (including abstract, but excluding references) and up to 6 keywords.

Manuscript submission information:

You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact Professor Félix Ramos.

The journal’s submission platform (Editorial Manager^®) is now available for receiving submissions to this Special Issue. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI: FoDL” when submitting your manuscript online. Both the Guide for Authors and the submission portal can be found on the Journal Homepage here: https://www.journals.elsevier.com/cognitive-systems-research

Manuscript Submission Deadline: 31^st December 2022

Editorial Acceptance Deadline: 30^th June 2023

Learn more about the benefits of publishing in a special issue: https://www.elsevier.com/authors/submit-your-paper/special-issues

Interested in becoming a guest editor? Discover the benefits of guest editing a special issue and the valuable contribution that you can make to your field: https://www.elsevier.com/editors/role-of-an-editor/guest-editors

31 May 2022

Brain-Inspired Cognitive Architectures for Artificial General Intelligence

Artificial General Intelligence (AGI) is expected to produce solutions to many important problems that require a true human level of social, emotional, commonsense, and other forms of general intelligence: from human care to urban security and beyond. The key role of Brain-Inspired Cognitive Architectures (BICA) is in scaffolding the AGI development. Therefore, this special issue aims to attract researchers from AGI, from the BICA community, and from all fields of Artificial Intelligence, as well as from Computational (and not only) Neuroscience, Cognitive Psychology, Neuromorphic Electronics, and other involved areas such as Neuroeconomics, Social and Educational Sciences, Computational Linguistics and Natural Language Processing, Data Sciences, and Cybersecurity to discuss the current state of BICA research from theoretical, modeling, and implementation perspectives in the context of the goals of AGI.

Guest editors:

Professor Félix Ramos, Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV)

Special issue information:

This special issue aims to attract researchers from Artificial General Intelligence (AGI), from the BICA community, and from all fields of Artificial Intelligence (AI), as well as from Computational (and not only) Neuroscience, Cognitive Psychology, Neuromorphic Electronics, and other involved areas such as Neuroeconomics, Social and Educational Sciences, Computational Linguistics and Natural Language Processing, Data Sciences, and Cybersecurity to discuss the current state of research on Brain-Inspired Cognitive Architectures from theoretical, modeling, and implementation perspectives in the context of the goals of AGI.

While the general consensus on a formal definition of AGI goals is still missing, we have a good intuitive understanding of the intelligent elements and cognitive functions that an AGI needs; among them are: perception, awareness, planning, reasoning, goal setting, memory, problem solving, natural language communication, creativity, emotions, and human-analogous social relationships. In fact, what we hope from an AGI perspective is that at least we should be able to create a solution to the problems we face every day.

Artificial General Intelligence, or AGI, is intended as a general-purpose intelligence. Today the term AGI stands as a synonym of Strong AI. By definition, AGI can learn and improve to efficiently perform all essential intelligent tasks and cognitive functions that a human can do, demonstrating human-level or superhuman cognitive abilities. AGI should be able to augment virtually any intelligent system with human-level or superhuman comprehensive knowledge and cognitive computing capabilities that would allow it to better access and process massive data. Therefore, the first part of the challenge for AGI is to perform virtually any intellectual tasks similarly or better than humans. Another part of the AGI Challenge is a human-analogous generalization ability in multiple cognitive dimensions. We hope that other parts of the AGI Challenge will be identified during the conference.

Currently, AGI follows two approaches: the first takes inspirations from biological evidence, while the second uses other sources of inspiration, such as methods of statistics, formal logics, and so on. The focus of this forum is on the first approach per se and on its role in the second approach. For example, many researchers agree today that deep learning of neural networks intended for human-related applications needs to be scaffolded by cognitive models derived from human psychology, therefore, by BICA.

Studies in Neuroscience and Psychology have produced sufficient evidence to understand basic human and animal behavior. Taking this evidence, researchers developed cognitive architectures that support basic cognitive functions like decision-making, planning, attention control, visual, auditory, and somatosensory information processing. These cognitive architectures bring to life hardware and software computer systems showing intelligent behavior. However, despite the evidence produced by these disciplines, there is still a significant number of fundamental problems that remain open, waiting for proposals from different scientific perspectives. Among the higher-level cognitive abilities that still await their AGI solutions are general context understanding, goal setting, social emotional intelligence, human-like active learning, human-level creativity. Today it is clear SI Proposal Form that these are among the objectives of AGI. There is still a long way to solving the actual AGI Challenge. Therefore, we need more events and venues where all possible sources of inspiration come together in a brainstorm and contribute to the design and creation of a fully functional AGI.

Manuscript submission information:

You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact Professor Félix Ramos.

The journal’s submission platform (Editorial Manager®) is now available for receiving submissions to this Special Issue. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI: BICA for AGI” when submitting your manuscript online. Both the Guide for Authors and the submission portal can be found on the Journal Homepage here: https://www.journals.elsevier.com/cognitive-systems-research

Timeline:

Manuscript Submission Deadline : December 15, 2022

Editorial Acceptance Deadline : January 31, 2023

Keywords:

Biologically Inspired Cognitive Architectures, Cognitive Modeling, Neuromorphic Electronics, Computational Neuroscience, Intelligent Agents, Artificial Creativity, Emotional Intelligence, Affective Computing, Integration of Cognitive Functions, Human-Analogous Learning, Multimodal Human-Computer Interaction, Cognitive Robotics, XR Cognitive Systems.

Learn more about the benefits of publishing in a special issue: https://www.elsevier.com/authors/submit-your-paper/special-issues

23 May 2022

Special Issue on Neural-Symbolic Cognitive Architectures

This special issue aims to attract researchers from Artificial Intelligence, Computational Neuroscience, Psychology, and Cognitive Robotics to discuss the current state of research on Neural and/or Symbolic Cognitive Architectures, both from theoretical and modelling perspectives.

Guest editors:

Dr. Aleksandr Panov

Moscow Institute of Physics and Technology (National Research University)

Special issue information:

Neural network models achieved impressive results in many areas of Artificial Intelligence: in image processing, natural language understanding, and reinforcement learning. However, many tasks solvable by rigorous symbolic methods, such as sequential decision-making, representation of conceptual knowledge, and modeling of reasoning, are solved unreliably or not solved at all by connectionist models. In addition, the symbol grounding problem, identified back in 1990 by Harnad, still dominates research topics in the field of Artificial Intelligence.

This collection is intended to provide a showcase of the state of the art and new ideas in the field of neuro-symbolic integration in order to identify promising directions and notable advances in this field. Another goal is to put developed methods and algorithms in the general context of research on cognitive systems, models, and cognitive architects, to clarify the role and essential place of integrating approaches.

Tentative list of topics covered by this special issue is:

Neural-Symbolic Integration approaches
Symbol grounding problem
Reinforcement learning methods in cognitive systems
Hybrid knowledge representation
Vector-symbolic architectures
Applied semiotics and semiotic cognitive architectures
Cognitive and Social Robotics
Integrated models of Learning and Reasoning
Biologically inspired cognitive architectures
Emotionally intelligent agents
Simultaneous Learning and Planning
Human-analogous active learning
Artificial and collaborative creativity
Explainable AI models and systems
General theory of neural-symbolic computation

Manuscript submission information:

You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact Dr. Aleksandr Panov

The journal’s submission platform (Editorial Manager®) is now available for receiving submissions to this Special Issue. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI: NS CognitiveArchitecture” when submitting your manuscript online. Both the Guide for Authors and the submission portal can be found on the Journal Homepage here: https://www.journals.elsevier.com/cognitive-systems-research

Timeline:

Manuscript Submission Deadline : August 31, 2022

Learn more about the benefits of publishing in a special issue: https://www.elsevier.com/authors/submit-your-paper/special-issues