Efren Mezura

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In this paper we present a comparison between six novel approaches to the fundamental problem of cyclic instability in Ambient Intelligence. These approaches are based on different optimization algorithms, Particle Swarm Optimization (PSO), Bee Swarm Optimization (BSO), micro Particle Swarm Optimization (μ-PSO), Artificial Immune System (AIS), Genetic(More)
Cyclic instability is a problem that, despite being shown to affect intelligent environments and in general any rule-based system, the strategies available to prevent it are still limited and mostly focused on centralized approaches. These approaches are based on topological properties of the Interaction Network (IN) associated , and locking a set of(More)
In this paper the problem of cyclic instability in dynamic environments is presented. This cyclic instability is generated when binary rule-based nomadic agents (agents entering or leaving the environment) interact in complex ways, generating undesirable outputs for the final user. Our strategy is focused on minimizing this cyclic behaviour, using(More)
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