Call For Paper

Call For Paper

Complexity

Bio-Inspired and Evolutionary Computation Approaches towards coping with Complexity in Human Machine Interaction

 

Intelligent systems for human-robot interaction are not only expected to automatically acquire and manage knowledge through a variety of sensors but also to learn, adapt and optimize their behaviour over time. Motivated by exciting and successful advances, biologically inspired models are becoming the choice in machine learning and computational intelligence to solve complex problems in a variety of applications. It goes from extraction of mid- and high-level abstract features, recognition tasks, optimization problems and more. This Special Issue will focus attention on approaches based on complex adaptive systems in nature such as artificial neural networks; evolutionary algorithms; game theory; adaptive programming; and chaos theory towards coping with complexity in Human-Machine Interaction (HMI). Examples include: human behaviour, emotional state and other bio-signals analysis and recognition, which can be used to learn and monitor normal and anomalous actions/activities and also health related issues (e.g. physical and emotional problems during human-machine interaction). Automated human behaviour and emotional state analysis has been, and still remains a challenging problem in socially assistive robotics.

 

Thus, this Special Issue aims to attract high original research articles related to how biologically inspired methods and evolutionary computation can help coping with complexity in HMI-based applications, such as health care, surveillance and Human-Robot Interaction (HRI).  Novel and innovative contributions including reviews related to bio-inspired and adaptive approaches are also welcome.

 

Potential topics include, but are not limited to:

 

    • Complex adaptive systems for Human-Machine Interaction (HMI) applications
    • Complex evolutionary computation for behaviour analysis/recognition
    • Bioinspired approaches for complex human activity recognition
    • Bioinspired approaches for socially assistive robotics in complex scenarios
    • Deep learning for advanced affective computing
    • Bioinspired approaches for Brain Computer Interfaces (BCI) and complex biosignal processing
    • Biologically inspired methods for artificial perception in Human-Robot Interaction (HRI) in complex environments



Submission Deadline     Friday, 14 December 2018

Publication Date                May 2019 

 

Papers are published upon acceptance, regardless of the Special Issue publication date.

 

 

Lead Guest Editor

 

Kamrad Khoshhal Roudposhti, Islamic Azad University - Lahijan Branch, Lahijan, Iran; kamrad@isr.uc.pt


Guest Editors

 

Diego R. Faria, Aston University, Birmingham, UK; d.faria@aston.ac.uk

 

Hadi Ali Akbarpour, University of Missouri, Columbia, USA; akbarpour@missouri.edu


Luis J. Manso, University of Extremadura, Badajoz, Spain; lmanso@unex.es