Function approximation can improve the ability of a reinforcement learner. Tile coding and Kanerva coding are two classical methods for implementing function approximation, but these methods may give poor performance when applied to large-scale, high-dimensional instances. In the paper, we evaluate a collection of hard instances of the predator-prey pursuit problem, a classic multi-agent reinfo...

One of the most widely used techniques for solving the famous localization problem in wireless sensor networks (WSNs) is the Trilateration. This paper introduces an enhanced version of the Trilateration algorithm entitled Fuzzy Based Trilateration (FBT). The main objective is to estimate the position of sensor nodes in WSNs accurately with a cheap, low power and simple technique. FBT achieves i...

In many modern data analysis scenarios the first and most urgent task consists of reducing the redundancy in high dimensional input spaces. A method is presented that quantifies the discriminative power of the input features in a fuzzy model. A possibilistic information measure of the model is defined on the basis of the available fuzzy rules and the resulting possibilistic information gain, as...

The shape of if-part fuzzy sets affects how well feedforward fuzzy systems approximate continuous functions. We explore a wide range of candidate if-part sets and derive supervised learning laws that tune them. Then we test how well the resulting adaptive fuzzy systems approximate a battery of test functions. No one set shape emerges as the best shape. The sinc function often does well and has ...

Today's competitive world has led managers to shift from traditional management to scientific management. Supply chain management is one of key issues in industries because, considering a high number of competitors in today's competitive world, competition has been extended from company level to the level of competition on their supply chain. For any organization seeking to achieve its goals in...