While several unified theories of cognition have been proposed, no framework has been established with the same degree of universal agreement as in biology and physics. A universal model of cognition is needed to direct research, push cognitive sciences, and test more or less realistic interventions on shifting environments. Here, we propose the necessary components for modelling a socially oriented, generative, and adaptive agent. We argue such a model requires modules for information input, management, storage, and use in order to grow an agent capable of human-like adaptive, socio-cultural behavioural strategies. We further argue that such an agent may be tested in different contexts through Agent-Based Modelling.

Like most organizations, you want to embed analytics insights in your operational processes and promote a culture of analytical decision making. You want to use machine learning, deep learning, and related technologies to automate decision making when and where it makes sense. These goals might seem both realistic and attainable. After all, software and cloud vendors are pitching you easy-to-use, quasi-automated, self-service tools and consultants promise to help you bridge the gap between the skills you have and the skills they say you'll need. Far from it, says Mark Madsen, a research analyst with information management consultancy Third Nature.