Invited speakers


A. Berthoz

Prof. Alain Berthoz

Honorary Professor at Collège de France & Member of the French Academy of Science and Academy of Technology.

Simplexity and vicariance. On human cognition principles for man-machine interaction

The study of living bodies reveals that in order to solve complex problems in an efficient, fast and elegant way, evolution has developed processes that are based on principles that are neither trivial nor simple. I called them "simplexes". They concern for example detours, modularity, anticipation, redundancy, inhibition, reduction of dimensionality etc. They often use detours that seem to add an apparent complexity but which in reality simplifies problem solving, decision and action. Among these general principles, "vicariance" is fundamental. It is the ability to solve some problem by different processes according to the capacity of each one, the context, etc. It is also the ability to replace a process by another in the case of deficits. It is also the possibility to create new solutions. Indeed, it is the basis of creative flexibility. I will give examples borrowed from perception, motor action, memory, spatial navigation, decision-making, relationship with others and virtual worlds. I will show its importance for the compensation of neurological deficits and the design of humanoid robots for example. Finally, I will mention their importance in the fields of learning and education.


M. Chetouani

Prof. Mohamed Chetouani

Professor at Pierre and Marie Curie University, France.

Interpersonal Human-Human and Human-Robot Interactions

Synchrony, engagement and learning are key processes of interpersonal interaction. In this talk, we will introduce interpersonal human-human and human-machine interactions schemes and models with a focus on definitions, sensing and evaluations at both behavioral and physiological levels. We will show how these models are currently applied to detect engagement in multi-party human-robot interactions, detect human’s personality traits and task learning.


A. Oulasvirta

Prof. Antti Oulasvirta

Associate Professor at Aalto University, Finland.

Can Machines Design? Optimizing User Interfaces for Human Performance

Algorithms have revolutionized almost every field of manufacturing and engineering. Is interaction design the next? This talk will give an overview of what future holds for algorithmic methods in interaction design. I will introduce the idea of using predictive models and simulations of end-user behavior in combinatorial optimization of user interfaces. I will demonstrate it with an interactive layout optimizer, provide an overview of research results, and provoke a critical discussion on the potentials and pitfalls of this approach.
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