Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Communications of the ACM
WET-ICE '96 Proceedings of the 5th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WET ICE'96)
Moving up the information food chain: deploying softbots on the world wide web
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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The question addressed in this paper is how do complex networks survive competitive forces and hostile attacks. In particular we seek to understand survivability and defence in large-scale computing networks. An integrated network of software agents is proposed as a solution to creating a dynamic immunological defence mechanism within such computing networks.In order to investigate these processes a multi-agent simulation model has been developed which demonstrates spontaneous group formation and the maintenance of group integrity. These system aspects are proposed as integral components of survivability. Each agent is susceptible to virus infections, passed between each agent and social assimilation by its local neighbours. From this model we observe a wide range of complex social behaviours that could be selected from a few critical interaction parameters. We then introduced an artificial immune system to each agent, which allows learned 'antibody' solutions to be exchanged between the agents within a social group. This mechanism reduced the infection level to a small percentage of the non-cooperative state. Finally, the paper considers the specific problem of how we might utilise such knowledge to develop a fully implemented network defence system.