Local-global coupling in strategy games: extracting signatures and unfolding dynamics

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.