Interactions between cognitive et emotional processes: a study in neuromimetic mobile and social robotics
Marwen Belkaid · HAL (Le Centre pour la Communication Scientifique Directe) · 2016
The purpose of my thesis is to study interactions between cognitive and emotional processes through the lens of neuromimetic robotics. The proposed models are implemented on artificial neural networks and embodied in robotic platforms -- forming situated systems. In general, the interest is twofold: 1) taking inspiration from biological solutions to design systems that better interact with their physical and social environments, and 2) providing computational models as a means to better understand biological cognition and emotion. The first part of the dissertation addresses spatial navigation as a framework to study biological and artificial cognition. In Chapter 1, I present a brief overview of the literature on biologically inspired navigation. Then, two issues are more specifically tackled. In Chapter 2, visual place recognition is addressed in the case of outdoor navigation. In that matter, I propose a model based on the notions of visual context and global precedence combining local and holistic visual information. Then, in Chapter 3, I consider the interactive learning of navigation tasks through non-verbal human--robot communication based on low-level visuomotor signals. The second part of the dissertation addresses the central question of emotion--cognition interactions. In Chapter 4, I give an overview of the research on emotion as a cross-disciplinary enterprise, including psychological theories, neuroscientific findings and computational models. In Chapter 5, I propose a conceptual model of emotion--cognition interactions. Then, various instantiations of this model are presented. In Chapter 6, I model the perception of the peripersonal space when modulated by emotionally valenced sensory and physiological signals. Last, in Chapter 7, I introduce the concept of Emotional Metacontrol as an example of emotion--cognition interaction. It consists in using emotional signals elicited by self-assessment to modulate computational processes -- such as attention and action selection -- for the purpose of behavior regulation.In this thesis, a key idea is that, in autonomous systems, emotion and cognition cannot be separated. Indeed, it is becoming well admitted that emotion is closely related to cognition, in particular through the modulation of various computational processes taking place in the brain. This raises the question of whether this modulation occurs at the level of sensory processing or at the level of action selection. In this thesis, I will advocate the idea that artificial emotion must be integrated in robotic architectures through bidirectional influences with sensory, attentional, decisional and motor processes. This work attempts to highlight how this approach to internal emotional processes can foster efficient interactions with the physical and social environment.