The results of this study show that there are many ways teachers can motivate students to learn at SMK Negeri 1 Palu after the earthquake, among others, by using various methods and activities. Because when teacher uses same method continuously it cause boredom reduce enthusiasm for learning students. Furthermore, also increase motivation making active. After earthquake gave more prizes who had...

Reinforcement learning provides both qualitative and quantitative frameworks for understanding and modeling adaptive decision-making in the face of rewards and punishments. Here we review the latest dispatches from the forefront of this field, and map out some of the territories where lie monsters.

In this paper we present a novel framework that allows a mobile robot to represent the environment and learn a task. The representation is a 'lazy map' in which observation are stored. Reinforcement learning is used to enable a human teacher to train the robot using rewards and punishments.

In this paper we implement an echo state network within the concept of actor-critic design to obtain optimal control policy for a mobile robot. The robot is asked to anticipate future rewards/punishments and react accordingly. Experimental results show that the proposed approach is simple and effective.

Learning to predict rewarding and aversive outcomes is based on the comparison between predicted and actual outcomes (prediction error: PE). Recent electrophysiological studies reported that during a Pavlovian procedure some dopamine neurons code a classical PE signal while a larger population of dopaminergic neurons reflect a "salient" prediction error (SPE) signal, being excited both by unpre...

Although positive incentives for cooperators and/or negative incentives for free-riders in social dilemmas play an important role in maintaining cooperation, there is still the outstanding issue of who should pay the cost of incentives. The second-order free-rider problem, in which players who do not provide the incentives dominate in a game, is a well-known academic challenge. In order to meet...