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Long-term memory plays a crucial role in learning mechanisms. We start to build up a probability model of learning (ENKI) ten years ago based on findings of micro genetics published in [1]. We accomplished a number of experiments in our department to testify the validity of the model with success. We described ENKI in detail here, giving the general mathematical formula of the learning curve. This paper pointed out that the model ENKI can detect its own strategy of learning in the brain as well as the simulation of the process of learning that will lead to the development of this method using its own strategy.

The loosely symmetric model (LS) is as a subjective probability model that came from human beings’ cognitive characteristics. To suggest a value to apply human beings’ cognitive characteristics, we developed a value function “loosely symmetric model with variable reference” (LS-VR) that expanded LS in the decision-making. It is important how get a reference value having an agent from environment to determine whether an algorithm using LS-VR explores in comparison with a reference value. In this study, we proposed using statistical knowledge in an online method to acquire a reference value. Therefore we succeeded in making the result that new method exceeded a superior existing model in the multi-armed banded problem that is a kind of decision-making problems.

Intelligent transportation system (ITS) uses electronic technologies such as information and communication technologies to improve the efficiency of transportation management. In the theoretical framework of gas‐kinetic traffic flow model, the probability of capable passing is essential for ITS. The probability of capable passing is assumed be a linear function of the traffic concentration, indicating that the probability of capable passing decreases proportionally with an increasing concentration. This work improves the model by introducing the speed desired by the driver into the original two‐lane cellular automata (CA) model. This study also examines the accuracy of the linearity assumption. A capable passing principle is established to simulate the capable passing probability for different concentrations and can be embedded in a system on chip of ITS.