Unit:
Κατεύθυνση Αλγόριθμοι, Λογική και Διακριτά Μαθηματικά (Α.Λ.ΜΑ.)Πληροφορική
Supervisors info:
Δημήτριος Θηλυκός: Καθηγητής, Τμήμα Μαθηματικών, ΕΚΠΑ
Μιχαήλ Δρακόπουλος: Είκουρος καθηγητής, Τμήμα Μαθηματικών, ΕΚΠΑ
Δημήτριος Ζώρος: Ακαδημαϊκός υπότροφος, Τμήμα Πληροφορικής και Τηλεπικοινωνιών, ΕΚΠΑ
Original Title:
Contributions of Graph Theory and Algorithms to Animal Behaviour and Neuroscience
Translated title:
Contributions of Graph Theory and Algorithms to Animal Behaviour and Neuroscience
Summary:
Graph theory and algorithms offer precious toolboxes for the modelling as well as the analysis
of numerous phenomena in natural sciences. Here a review of the modern bibliography is pre-
sented, divided in four main chapters, giving some indications on how the concepts of these two
disciplines can be used for the study of animal behaviour and neuroscience. As an exception
the premier part of the first chapter provides a short discussion on the applications of graph
theory on molecular biology. This choice made in order to make this work more complete and
give to the readers from various backgrounds an, as much as possible, overall view of the future
potential of such interdisciplinary approaches. The rest two sections of the first chapter deals
with brain networks and central terms of graph theory, such as centrality, in their study. The
second chapter introduces some concepts of animal sociality and refers to studies of animal
cooperation, focusing on evolutionary graph and game theory. Moreover, in the last section of
this chapter the collective motion of animal groups is discussed providing, into the bargain, an
introduction of basic terms for the subsequent third chapter. Interdisciplinary research, aiming
to unite methods from different fields, is vastly used in order to answer biological questions.
Although, as it is presented below, both the fields of algorithms and biology can contribute to
the elaboration of each other. Hence, the third chapter provides information about algorithms
whose design has been inspired by the (collective) behaviour of animals in the nature. Finally,
the fourth chapter deviates anew from the central focus of the previous chapters and makes a
short introduction in the substantial controversial computational nature of cognition and by
extension behaviour. Overall, one can observe that the cooperation of the above mentioned
fields is extensive while the accomplished research opens new questions which can be studied
only in the light of such collaborations.
Main subject category:
Science
Keywords:
Social, network, collectiive, behaviour, algorithm, cooperation, game,
Number of references:
201
