Human Behavior, Emotion and Representation

Dear Colleagues,

Natural behavior skills based on cognitive abilities are key challenges for robots, virtual agents and intelligent machines while interacting with humans. This becomes particular evident by the expected increase in the use of intelligent interaction partners designed to support humans in everyday situations within the next coming decade (such as virtual coaches, companion robots, assistive systems and autonomous cars). These systems will need to develop their autonomy and they have to elicit social interaction and social synchrony. In order to achieve these goals, their perception of humans, as well as their behavior, must build on more complex inputs about emotion, mental state and models of the human partners compared to the mainly more low-level based approaches currently in use. Recent advances in multidisciplinary research on behavior, emotional states, visual behavior, neurofeedback, physiological parameters or mental memory representations help to understand the cognitive background of action and interaction in everyday interactions and therefore to pave the way for the design of new building blocks for a more natural and intuitive human-machine interaction.

This special issue focuses on building blocks of human/agent(s) interactions. Collecting and analyzing multi-modal data from different measurements also allows constructing solid computational models. These blocks of interaction will serve as basis for building artificial cognitive systems being able to interact with humans in an intuitive way and to acquire new skills by learning from the user. This will result in new forms of human-computer interaction such as individualized, adaptive assistance systems for scaffolding cognitive, emotional and attentive learning processes. In this context, it is clearly advantageous for intelligent robots and virtual agents to know how these cognitive representations and physiological parameters are formed, stabilized and adapted during different phases in daily actions. This knowledge enables a technical system to specify and perceive individual’s current level of learning and performance, and therefore to shape the interaction. These interactions must be (socially) appropriate, not excessive. Such systems can assist users in developing (interaction) skills in a variety of domains and during different phases in daily-life actions. At the same time, interactive systems should fulfill constraints such as usability, acceptability and ethics.

Topics of interest of this special issue include all aspects of affective computing dedicated to robotics and interactive systems including, but not limited to, the following topics:

• Acoustic, visual or multimodal processing for affect recognition
• Real time and embedded perception into the wild
• Human Behavior analysis
• Anticipation and Imitation of Human Behavior
• Affects and social interaction modeling
• Affective computing in the human/robot interaction loop
• Affects rendering and synthesis
• Acceptability and usability while interacting
• Affects in developmental robotics
• Computational modeling of cognitive interaction components
• Case Studies and Applications in Real-life Contexts

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