Cognitive Twin: A Cognitive Approach to Personalized Assistants

This paper presents an analysis of a cognitive twin, implemented in a cognitive architecture. The cognitive twin is intended to be a personal assistant that learns to make decisions from your past behavior. In this proof-of-concept case, we have the cognitive twin select attendees to a party, based upon what it has learned (through ratings) about an agent's social network. We evaluate two versions of a model with respect to rate of change in the social network, the noise in the rating data, and the sparsity of the data.