Cognitive Systems Research: Special Issue on Biologically Inspired Cognitive Architectures: Papers from the Tenth Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2019).

Abstract

This Special Issue of Cognitive System Research on Biologically Inspired Cognitive Architectures: Papers from the Tenth Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2019) have solicited and collected research papers in all domains of science and technology that directly or indirectly may help us to make an advance toward the BICA Challenge, which is to implement the top essential functionality of the human mind in a machine. The selected papers included here are based on presentations given from 16 to 18 August 2019 during the 10th Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2019) held at the Microsoft Main Campus in Seattle, USA. This issue of the journal Cognitive Systems Research continues the new series of special issues: on Brain-Inspired Cognitive Architectures for Artificial Intelligence (BICA*AI). In particular this volume is composed of a selection of papers and contains a wide variety of ideas and approaches, all centered around the theme of understanding how to create general-purpose humanlike emotional artificial intelligence framework using biological inspirations. Models of Emotional Cognitive Architectures are presented under different and interesting perspectives. Samsonovich addresses an approach to extend the general framework of emotional Biologically Inspired Cognitive Architecture (eBICA) framework to modeling human social-emotional intelligence. Tikhomirova et al. study the dynamics of human emotional states in the process of social interaction in a virtual environment. Nieuwazny et al. present a statistical analysis of emotional and moral associations with Buddhist religious terms appearing on Japanese blogs. Rosales et al. propose a framework that represents an abstraction of the human emotion process usually included in Artificial Emotion System (AES). Ptaszynski et al. propose a method for specifying the emoticon's meaning ambiguity used by people during internet communication. Castellanos et al. describe a mechanism to model the influence of agents' factors on the emotional evaluation of stimuli in computational models of emotions. Lieto et al. propose a computational framework aimed at extending the problem-solving capabilities of cognitive artificial agents. Yalςin et al. create a framework to equip Embodied Conversational Agents (ECAs) with real time multi-modal empathic interaction capabilities. Other aspects of BICA Challenge are represented in this volume by Lopez et al. that propose a systematic review of non-invasive BCIs for controlling UAVs for Dealing with Attention Deficit-Hyperactivity Disorder, by Akimoto’s study of the analogical translation of Genette's narrative discourse theory into a cognitive system. Georgeon et al. propose the Constitutive Autonomy through Self-programming Hypothesis (CASH) framework. The work of Vityaev demonstrates that brain might reflect the external world causal relationships. Schmidtke presents a logic-based system for generating visuospatial representations from textual input. Utz et al. prove how a time-based AI created media can be used to explore the nature of the human visual system. Vandesompele et al. demonstrate the feasibility of using populations of spiking neurons for a compliant robot. Sychev et al. show an automatic grading and hinting in open-ended text questions. Howard Schneider proposes how the Meaningful-Based Cognitive Architecture (MBCA) can offers an explanation about the schizophrenia paradox. Overall, the volume presents a pleasant overview with contributions from many countries depicting all major topics in BICA Challenge research. Personally, I am very pleased to have served as guest editor, and I am convinced that these papers can provide inspiration for new researchers who will approach the challenge of creating Brain-Inspired Cognitive Architectures for Artificial Intelligence (BICA*AI).