Artificial General Intelligence (AGI) is the emerging field of building of "thinking machines", that is, general-purpose systems with intelligence comparable to that of the human mind. While this was the original goal of Artificial Intelligence (AI), the mainstream of AI research has turned toward domain-dependent and problem-specific solutions; Artificial General Intelligence refers to systems that aim to understand human cognition by building generally intelligent AI systems, and vice versa, to use our growing understanding of all areas of cognition to advance the development of artificial minds. Similar labels for this kind of research include "Strong AI" and "Human-level AI". The rapid advances of AI during the last years were mainly driven by the progress of learning systems. Reinforcement learning, and supervised and unsupervised learning, have given us systems that can ground their interaction with the world in rich sensory data, discover categories and policies, map images and video to linguistic labels, and enable countless new applications from knowledge management to game playing, and from mobile agents to self-driving cars. In spite of this tremendous progress, these new systems fail to reach the autonomous activity, complex structure and creativity of human minds. One of the most important components of generally intelligent systems will be a detailed model of motivation. Motivation may not only structure the formation of categories and deliver rewards and utility functions for policy search and decision making; it may also contribute to the self-organization of a cognitive architecture during developmental processes. The parametrization of motivation can help model and understand trait differences in cognitive processing. Motivation can also drive discovery of social, communicative, cognitive and physiological goals. A core component and underlying mechanism of motivation is emotion. Emotion can be conceptualized in various ways, including as valenced responses to environmental and internal events and expectations, and as the modulation and configuration of the cognitive system as a whole. Computational models of emotion are being developed for both basic research purposes (e.g., to understand the mechanisms mediating emotion generation and affective biases, to understand the role of emotions in creativity), and more applied purposes. The latter models can enhance user modeling, enable more accurate models of human behavior for social simulations and provide more realistic and effective agent architectures for virtual characters in both serious and entertainment games. Recently, the field Artificial General Intelligence has seen a number of contributions focusing on understanding motivation and emotion. We wish to invite novel and recent developments in this area, to edit a special issue of the Journal of Artificial General Intelligence that explicitly focuses on computational models of motivation and emotion. Recommended Topics The topics we invite include but are not limited to:
The contributions should be novel, original, of high technical quality, and of interest to the community of AGI researchers. In addition to descriptions of existing models, we also invite speculative and philosophical contribution at a high technical standard, as long as they significantly advance our understanding of how to build generally intelligent systems. Submission Procedure Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere (AGI Conference contributions will be considered if they are sufficiently expanded for journal publication). Submissions should have a length of 12-30 pages, and use the supplied templates (LaTeX or MS Word). Interested authors should consult the website for manuscript submissions http://jagi.mindmakers.org/ prior to submission. All submissions will undergo standard peer review process. All submissions must be submitted via http://jagi.mindmakers.org/index.php/jagi/index. Accepted contributions will be published in the JAGI special issue "Artificial Intelligence Models of Motivation and Emotion". (The current publication charge is $100, and can be waived in case of hardship.) Deadline: May 15, 2017 Editors of the special issue: Dr. Joscha Bach, Harvard Program for Evolutionary Dynamics, Cambridge Dr. Eva Hudlicka, Principal Scientist at Psychometrix Associates; Visiting Lecturer at College of Information and Computer Sciences, University of Massachusetts-Amherst Prof. Stacy C. Marsella, Professor, Departments of Psychology and College of Computer and Information Science, Northeastern University, Boston |
ISSN: 1946-0163