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The purpose of this paper is to present a macroeconomic model, in which the bank determine the loan interest rate and the deposit interest rate by assuming the loan demand curve and the deposit supply curve. The bank adjusts the loan interest rate and the deposit interest rate while observing the difference between the assumed demand for loan and the actual demand for loan.

Taiwan has not yet been singed the “Convention on Nuclear Safety; CNS” that was adopted by the International Atomic Energy Agency （IAEA） in 1994. However, if these international activities help promote nuclear safety, Taiwan must participate in it and fulfill its related obligations. Therefore, despite Taiwan being a non-member state to the CNS, it is required by the Convention to act as a member state to meet all the requirements addressed in the CNS. Ensuring the public trust of nuclear safety regulations in the most important policy issue for the location, operation, waste disposal and off-commissioning of nuclear power plants, etc. As part of an international comparison of nuclear safety regulatory bodies in the East Asian region, this note organizes and evaluates the independence and transparency of Taiwan’s regulatory bodies.

The Japanese Bridge Management System (J-BMS) RC version consists of the following three subsystems: (1) a bridge maintenance database system (J-BMS DB), (2) a concrete bridge rating expert system (RC-BREX) and (3) a maintenance plan optimization system (MPOS). Especially, in this paper, the RC-BREX system for deteriorating concrete bridges is described based on how to construct from a hierarchical neural network in order to carry out fuzzy inference and machine learning by using the neural network with the back-propagation method. Furthermore, the comparisons between diagnostic results by bridge experts and those of the proposed system are presented so as to demonstrate the validity of the system’s learning capability by using the training set for machine learning which obtained from inspection on actual in-service bridges and questionnaire surveys by bridge experts.

We investigate symmetric equilibria of mutual reinforcement learning when both players alternately learn the optimal memory-two strategies against the oppo-nent in the repeated prisoners' dilemma game. We provide a necessary condi-tion for memory-two deterministic strategies to form symmetric equilibria. We then provide three examples of memory-two deterministic strategies which form symmetric mutual reinforcement learning equilibria. We also prove that mu-tual reinforcement learning equilibria formed by memory-two strategies are also mutual reinforcement learning equilibria when both players use reinforcement learning of memory-n strategies with n > 2.