This paper presents an exploration of the characteristics and structure of a cognitive architecture for control ofassisted living systems. The aspects of cognition considered are self-organization, communication, and inherited knowledge.A cognitive solution for a related problem, function optimization, is developed because of the complexity and size of the assistiveliving problem. Support for this approach stems from the artificial intelligence field where optimization is considered to be acritical aspect of cognition, and from the similarity between the performance metrics for the two problem domains. A searchalgorithm is developed using the bracketing and gradient methods as inherited knowledge. A key finding is that using a cognitivestructure caused the search to display aspects of the characteristics, behavior, and performance of human cognition. In terms ofperformance, the cognitive search converges faster than either the bracketing or gradient searches alone, and its feasible problemset is larger than the intersection of their individual sets. Similarly, human cognition acts quickly and can address a large setof dissimilar problems. This gives confidence that the guidelines distilled from the development of the cognitive search canproduce a similar level of performance when applied to an assistive living system. However, this paper does not address thedetails involved in actually implementing these guidelines on an assistive living system.
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