I am glad to post that Miguel Aguilera presented his PhD thesis and is now officially a doctor in cognitive science by the University of Zaragoza. His thesis “Interaction Dynamics and Autonomy in Cognitive Systems” is a rare, challenging, broad, audacious and brilliant contribution to the study of autonomous systems. How does a “self” or an “autonomous system” emerge and constitute itself through interactions with the environment? It seems the answer is impossible to provide, you need to have a self, an identity, before it starts interacting with the environment, but, at the same time, some forms of sensorimotor or cognitive identity emerge and sustain themselves through interactions. You are an example yourself: your identity is the result of your actions, and your actions are caused by you. How could this be? Can we formalize and model this type of emergence of autonomous organizations through interactions? This is the fundamental question addressed by Dr. Aguilera. And the results are innovative, profound, operational and insightful. The core of the thesis is a robotic model capable to switch spontaneously between different behavioural preferences, and whose control architecture is itself a novel contribution to robotics: a kuramoto oscillatory network whose connections plastically change so as to keep macroscopic relationships homeostatic. The robot is a system that is capable to maintain its own behavioural organization while shifting preferences. Nothing is hard-coded, the controller is designed using a carefully scaffolded evolutionary optimization algorithm that gave rise to a complex dynamical system that shows macroscopic properties that emerge from distributed interactive processes at different timescales.
But this is not the major contribution of the thesis.
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