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Copyright: Ghoneim, Ayman Ahmed Sabry Abdel Rahman
Copyright: Ghoneim, Ayman Ahmed Sabry Abdel Rahman
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Abstract
Complexity underlying life is largely governed by the dynamics of interaction
within and between living and nonliving entities. Evolutionary strategy games are extensively used in modelling and understanding complex behaviors in a wide range of fields including theoretical biology, social interactions, economics, politics, defense
and security. Strategy games are said to distill the key elements of interactions be-
tween real-world entities and organizations - one of the challenges lies in determining
the mapping of complex real life situation dynamics to that of a certain game. That
leads us to the two major research questions outlined below.
In this thesis, we are taking evolutionary games a step further to investigate
the interplay between local and global dynamics, where local dynamics are repre-
sented by locally pairwise interactions among the population's players governed by
the Iterated Prisoner's Dilemma game. To represent the global dynamics, two main
modelling ideas are proposed, in the first model; a mixed evolutionary game is in-
troduced where players are competing globally on the population level in a minority
game. The interplay between local and global dynamics in this model represents the
interplay between different scopes of competition between the same players. Sec-
ondly, we introduce a model for studying the effect of sharing global information
concerning a population of players, shedding light on how global information can
alter the emerging dynamics of local interactions.
Furthermore, the thesis addresses the question of whether games - with different
dynamics - have unique signatures (footprints) that can be used in recognizing and
differentiating among them, and whether these footprints are consistent along the
evolutionary path of these games. We show here that by building winning networks
between players, and determining network motifs of these winning networks, we
can obtain motifs' counts signals that are sufficient to categorize and recognize the
game's utility matrix used by the players. We also demonstrate that these footprints
- motifs' counts - are consistent along the evolutionary path of the games, due to
a hyper-cyclic behavior that exists between strategies. Finally, we show that this
approach is capable of identifying whether a certain population is driven by local
dynamics or both local and global dynamics using the proposed mixed game.