The analysis of embodied and situated agents form a dynamical system perspective is often
limited to a geometrical and qualitative description. However, a quantitative analysis is necessary
to achieve a deep understanding of cognitive facts.
The field of embodied cognition is multifaceted, and the first part of this thesis is devoted to exploring
the diverse meanings proposed in the existing literature. This is a preliminary fundamental
step as the creation of synthetic models requires well-founded theoretical and foundational
boundaries for operationalising the concept of embodied and situated cognition in a concrete
neuro-robotic model. By accepting the dynamical system view the agent is conceived as highly
integrated and strictly coupled with the surrounding environment. Therefore the antireductionist
framework is followed during the analysis of such systems, using chaos theory to unveil global
properties and information theory to describe the complex network of interactions among the
heterogeneous sub-components.
In the experimental section, several evolutionary robotics experiments are discussed. This class
of adaptive systems is consistent with the proposed definition of embodied and situated cognition.
In fact, such neuro-robotics platforms autonomously develop a solution to a problem exploiting
the continuous sensorimotor interaction with the environment.
The first experiment is a stress test for chaos theory, a mathematical framework that studies erratic
behaviour in low-dimensional and deterministic dynamical systems. The recorded dataset
consists of the robots’ position in the environment during the execution of the task. Subsequently,
the time series is projected onto a multidimensional phase space in order to study the underlying
dynamic using chaotic numerical descriptors. Finally, such measures are correlated and confronted
with the robots’ behavioural strategy and the performance in novel and unpredictable
environments.
The second experiment explores the possible applications of information-theoretic measures for
the analysis of embodied and situated systems. Data is recorded from perceptual and motor
neurons while robots are executing a wall-following task and pairwise estimations of the mutual
information and the transfer entropy are calculated in order to create an exhaustive map of the
nonlinear interactions among variables. Results show that the set of information-theoretic employed
in this study unveils characteristics of the agent-environemnt interaction and the functional
neural structure.
This work aims at testing the explanatory power and impotence of nonlinear time series analysis
applied to observables recorded from neuro-robotics embodied and situated systems.
Date of Award | 2018 |
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Original language | English |
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Awarding Institution | |
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Supervisor | Angelo Cangelosi (Other Supervisor) |
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Analysis of Embodied and Situated Systems from an Antireductionist Perspective
Da Rold, F. (Author). 2018
Student thesis: PhD