|Thesis abstract: |
How intelligence arises in humans is far to be completely unveiled. Understanding the brain mechanisms that make it possible is one of the most interesting and debated topics in neuroscience. However, recent advances speculate about that this is only half part of the story. Intelligent behaviours in humans could emerge from a good balance among several factors, namely, the brain, the body, sensors, actuators, and the environment. Even though no conclusive evidences about the truth of this theory are available, it is very promising.
Beyond the great relevance for science, the natural application of these studies is the robotics field. In the last decades, several approaches have been proposed to design intelligent machines on the basis of scientific findings, especially from neuroscience. The underlying idea of these approaches is to transfer knowledge from neuroscience and biomechanics to the designing of biologically inspired robots. Although the design of a mechanical structure mimicking the biological counterpart is still an affordable task, it becomes less true for the design of underlying
neural mechanisms both for controlling the body and for the emergence of cognition.
Even tough the biologically inspired robotics is a very active research field, several solutions have been proposed, from evolutionary approaches to developmental robotics. However, a solution that encodes on the same neural lattice low level computational mechanisms and the emergence of cognition is still missing.
In this thesis a comprehensive study of this topic is presented. First, I design several low level computational models composing the visual dorsal pathway, which is devoted to one of the most relevant functionalities provided by the brain: the reaching task. A comparison with the state of art is presented. Second, a comparison among previously developed models inspires the proposal for a common computational framework that should embody brain computational principles, such as population coding. Third, a biologically inspired cognitive architecture is proposed. The architecture develops a middle level of cognition, filling the gap be-
tween the low level computational mechanisms and symbolic reasoning.
This cognitive architecture is able to generate new goals and behaviours from previous ones, exploiting the synergy among the thalamus, the amygdala, and the cortex. Finally, a proposal for a roadmap towards a fully integrated biologically inspired architecture is presented. This architecture exploits the synergy between the low level computational mechanisms and the proposed cognitive architecture.