Local Interactions, Learning and Automata Networks in Games
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1998-09-13
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Virginia Tech
Abstract
This dissertation is an attempt of expanding the domain of game theory into the sphere of evolving, potentially non-equilibrium systems. We especially focus our attention on studying the effects of local interactions, using automata networks as a modelling tool.
The Chapters 2 and 3 of this dissertation concentrate on applications of the local nature of interactions and rely on automata networks as an investigating and modelling tool for game theory. Chapter 2 is devoted to cooperation and to a smaller extent to the endogenous formation of links between the agents. Chapter 3 is investigating the deterministic and stochastic best response play when interactions are local.
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Keywords
automata networks, learning, evolution, cooperation