Motivational behavior of neurons and fuzzy logic of brain: can robot have drives and love work?
Uziel Sandler, Lev E. Tsitolovsky · International Conference on Systems · 2006
Many theories relate to the brain as a complex network of neurons, which are approximated as simple elements that make summation of excitations and generate output reaction in accordance with simple activation functions. Such an idealization, however, is far from the properties of a real neuron. In this paper we present results of the experiments of a real neuron's learning and theoretical description this processes is based on Fuzzy Dynamics: contemporary theory operates with perceptions as with a mathematical object. We point out that logic of a neuron's decision-making may be close to the fuzzy logic. In the conclusion, we discuss possibility of design of a feeling robot, which will be able to use a trial-and-error self-learning process based on artificial motivations and effectively adapt (like an animal) its behavior in suddenly changing environmental conditions.