Monetary policy rule might be helpful to avoid the problem of time inconsistency provided there is a commitment to the rule. The commitment is the ability of a government to bind future policies. However, it doesn’t include intrinsic motivations. Therefore, hegemony, which includes both intrinsic and extrinsic motivations, better solves the problem of  time inconsistency. In this paper, we expl...

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but ar...

This paper aims to design an optimal distributed multi-agent controller for load frequency control and optimal power flow purposes. The controller parameters are optimized using Grey Wolf Optimization (GWO) algorithm. The designed optimal distributed controller is employed for load frequency control in the IEEE 30-bus test system with six generators. The controller of each generator is consider...

This paper estimates a sticky-information general-equilibrium model for the United States and the Euro-area, and uses it as a laboratory to answer monetary policy questions. The …rst set of questions is positive and concerns describing past monetary policy: what policy rule has best described policy? What has been the role of stabilization policy? How large have policy errors been? What is the ...

We consider an optimal investment problem when a firm such as an electric power company has the operational flexibility to expand and contract capacity with fixed cost. This problem is formulated as an impulse control problem combined with optimal stopping. Consequently, we obtain optimal investment timing, optimal capacity expansion and contraction timing, and the investment value. We also sho...

In knowledge discovery and data mining many measures of interestingness have been proposed in order to measure the relevance and utility of the discovered patterns. Among these measures, an important role is played by Bayesian confirmation measures, which express in what degree a premise confirms a conclusion. In this paper, we are considering knowledge patterns in a form of “if..., then...” ru...

Fusion is a popular practice to combine multiple classifiers or multiple modalities in biometrics. In this paper, optimal decision fusion (ODF) by AND rule and OR rule is presented. We show that the decision fusion can be done in an optimal way such that it always gives an improvement in terms of error rates over the classifiers that are fused. Both the optimal decision fusion theory and the ex...