11Sustainable Cognitive Engineering: Brain Modeling; Evolution of a Knowledge Base
11.1. Introduction
Every person displays many significant differences. How can we spot those which facilitate the emergence of a solution, a trouble, or a behavior?
Here, the question is to define how modeling a population in order to analyze, detect and/or estimate both a profitable or dangerous association and combinations. The second question is related to the update and enhancement of our decisional knowledge base in order to obtain a better sustainability [KEN 07].
To develop a sustainable cognition, it is difficult to base our way of thinking on already known paradigms. At the present time, we are faced with a problem of understanding how our brain is encoded, modeled and working. It is a question of structure and architecture: knowledge is not included in a memory cell, but embedded in a neural network at synapse level. It is also a question of technologies (cognitive computing vs. calculation computing). The question is to know what kind of statistical computing is implemented in the brain: is it a continuous or a quantum evolution we have to integrate?
In this chapter, we highlight some of these aspects and detail some techniques used in this area. We will successively discuss the following:
- – the sustainability concepts in cognitive computing;
- – probabilistic approaches in the brain;
- – brain structures and cognitive asymmetries;
- – brain and quantum physics, some properties;
- – several ...
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