13,351 research outputs found
Altruism in groups: an evolutionary games approach
We revisit in this paper the relation between evolution of species and the
mathematical tool of evolutionary games, which has been used to model and
predict it. We indicate known shortcoming of this model that restricts the
capacity of evolutionary games to model groups of individuals that share a
common gene or a common fitness function. In this paper we provide a new
concept to remedy this shortcoming in the standard evolutionary games in order
to cover this kind of behavior. Further, we explore the relationship between
this new concept and Nash equilibrium or ESS. We indicate through the study of
some example in the biology as Hawk and Dove game, Stag Hunt Game and Prisoner
Dilemma, that when taking into account a utility that is common to a group of
individuals, the equilibrium structure may change dramatically. We also study
the multiple access control in slotted Aloha based wireless networks. We
analyze the impact of the altruism behavior on the performance at the
equilibrium
Fault-tolerant wireless sensor networks using evolutionary games
This dissertation proposes an approach to creating robust communication systems in wireless sensor networks, inspired by biological and ecological systems, particularly by evolutionary game theory. In this approach, a virtual community of agents live inside the network nodes and carry out network functions. The agents use different strategies to execute their functions, and these strategies are tested and selected by playing evolutionary games. Over time, agents with the best strategies survive, while others die. The strategies and the game rules provide the network with an adaptive behavior that allows it to react to changes in environmental conditions by adapting and improving network behavior. To evaluate the viability of this approach, this dissertation also describes a micro-component framework for implementing agent-based wireless sensor network services, an evolutionary data collection protocol built using this framework, ECP, and experiments evaluating the performance of this protocol in a faulty environment. The framework addresses many of the programming challenges in writing network software for wireless sensor networks, while the protocol built using the framework provides a means of evaluating the general viability of the agent-based approach. The results of this evaluation show that an evolutionary approach to designing wireless sensor networks can improve the performance of wireless sensor network protocols in the presence of node failures. In particular, we compared the performance of ECP with a non-evolutionary rule-based variant of ECP. While the purely-evolutionary version of ECP has more routing timeouts than the rule-based approach in failure-free networks, it sends significantly fewer beacon packets and incurs statistically fewer routing timeouts in both simple fault and periodic fault scenarios
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